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A Smoothness Energy without Boundary Distortion for Curved SurfacesMay 23 2019Current quadratic smoothness energies for curved surfaces either exhibit distortions near the boundary due to zero Neumann boundary conditions, or they do not correctly account for intrinsic curvature, which leads to unnatural-looking behavior away from ... More

Significance of parallel computing on the performance of Digital Image Correlation algorithms in MATLABMay 15 2019Digital Image Correlation (DIC) is a powerful tool used to evaluate displacements and deformations in a non-intrusive manner. By comparing two images, one of the undeformed reference state of a specimen and another of the deformed target state, the relative ... More

DeepFlow: History Matching in the Space of Deep Generative ModelsMay 14 2019The calibration of a reservoir model with observed transient data of fluid pressures and rates is a key task in obtaining a predictive model of the flow and transport behaviour of the earth's subsurface. The model calibration task, commonly referred to ... More

Learning to EvolveMay 08 2019Evolution and learning are two of the fundamental mechanisms by which life adapts in order to survive and to transcend limitations. These biological phenomena inspired successful computational methods such as evolutionary algorithms and deep learning. ... More

Please Stop Permuting Features: An Explanation and AlternativesMay 01 2019This paper advocates against permute-and-predict (PaP) methods for interpreting black box functions. Methods such as the variable importance measures proposed for random forests, partial dependence plots, and individual conditional expectation plots remain ... More

Computer Science and Metaphysics: A Cross-FertilizationMay 01 2019Computational philosophy is the use of mechanized computational techniques to unearth philosophical insights that are either difficult or impossible to find using traditional philosophical methods. Computational metaphysics is computational philosophy ... More

Deep Learning for Audio Signal ProcessingApr 30 2019Given the recent surge in developments of deep learning, this article provides a review of the state-of-the-art deep learning techniques for audio signal processing. Speech, music, and environmental sound processing are considered side-by-side, in order ... More

A neural network based on SPD manifold learning for skeleton-based hand gesture recognitionApr 29 2019This paper proposes a new neural network based on SPD manifold learning for skeleton-based hand gesture recognition. Given the stream of hand's joint positions, our approach combines two aggregation processes on respectively spatial and temporal domains. ... More

Teaching AI, Ethics, Law and PolicyApr 29 2019The cyberspace and the development of new technologies, especially intelligent systems using artificial intelligence, present enormous challenges to computer professionals, data scientists, managers and policy makers. There is a need to address professional ... More

Towards Vulnerability Analysis of Voice-Driven Interfaces and Countermeasures for ReplayApr 13 2019Fake audio detection is expected to become an important research area in the field of smart speakers such as Google Home, Amazon Echo and chatbots developed for these platforms. This paper presents replay attack vulnerability of voice-driven interfaces ... More

Dungeons for Science: Mapping Belief Places and SpacesApr 10 2019Apr 11 2019Tabletop fantasy role-playing games (TFRPGs) have existed in offline and online contexts for many decades, yet are rarely featured in scientific literature. This paper presents a case study where TFRPGs were used to generate and collect data for maps ... More

Dungeons for Science: Mapping Belief Places and SpacesApr 10 2019Apr 29 2019Tabletop fantasy role-playing games (TFRPGs) have existed in offline and online contexts for many decades, yet are rarely featured in scientific literature. This paper presents a case study where TFRPGs were used to generate and collect data for maps ... More

Dungeons for Science: Mapping Belief Places and SpacesApr 10 2019Tabletop fantasy role-playing games (TFRPGs) have existed in offline and online contexts for many decades, yet are rarely featured in scientific literature. This paper presents a case study where TFRPGs were used to generate and collect data for maps ... More

Decomposition and Modeling in the Non-Manifold domainMar 30 2019The problem of decomposing non-manifold object has already been studied in solid modeling. However, the few proposed solutions are limited to the problem of decomposing solids described through their boundaries. In this thesis we study the problem of ... More

Trifocal Relative Pose from Lines at Points and its Efficient SolutionMar 23 2019Mar 28 2019We present a new minimal problem for relative pose estimation mixing point features with lines incident at points observed in three views and its efficient homotopy continuation solver. We demonstrate the generality of the approach by analyzing and solving ... More

Trifocal Relative Pose from Lines at Points and its Efficient SolutionMar 23 2019Apr 16 2019We present a new minimal problem for relative pose estimation mixing point features with lines incident at points observed in three views and its efficient homotopy continuation solver. We demonstrate the generality of the approach by analyzing and solving ... More

A Polynomial-time Solution for Robust Registration with Extreme Outlier RatesMar 20 2019We propose a robust approach for the registration of two sets of 3D points in the presence of a large amount of outliers. Our first contribution is to reformulate the registration problem using a Truncated Least Squares (TLS) cost that makes the estimation ... More

A New Lower Bound for Semigroup Orthogonal Range SearchingMar 19 2019We report the first improvement in the space-time trade-off of lower bounds for the orthogonal range searching problem in the semigroup model, since Chazelle's result from 1990. This is one of the very fundamental problems in range searching with a long ... More

Combining Model and Parameter Uncertainty in Bayesian Neural NetworksMar 18 2019Mar 20 2019Bayesian neural networks (BNNs) have recently regained a significant amount of attention in the deep learning community due to the development of scalable approximate Bayesian inference techniques. There are several advantages of using Bayesian approach: ... More

Combining Model and Parameter Uncertainty in Bayesian Neural NetworksMar 18 2019Bayesian neural networks (BNNs) have recently regained a significant amount of attention in the deep learning community due to the development of scalable approximate Bayesian inference techniques. There are several advantages of using Bayesian approach: ... More

Domain adaptation for holistic skin detectionMar 16 2019Human skin detection in images is a widely studied topic of Computer Vision for which it is commonly accepted that analysis of pixel color or local patches may suffice. This is because skin regions appear to be relatively uniform and many argue that there ... More

Dynamic Anonymized Evaluation for Behavioral Continuous AuthenticationMar 07 2019Emerging technology demands reliable authentication mechanisms, particularly in interconnected systems. Current systems rely on a single moment of authentication, however continuous authentication systems assess a users identity utilizing a constant biometric ... More

Breaching the Future: Understanding Human Challenges of Autonomous Systems for the HomeMar 04 2019The domestic environment is a key area for the design and deployment of autonomous systems. Yet research indicates their adoption is already being hampered by a variety of critical issues including trust, privacy and security. This paper explores how ... More

Practical Prediction of Human Movements Across Device Types and Spatiotemporal GranularitiesMar 03 2019Understanding and predicting mobility are essential for the design and evaluation of future mobile edge caching and networking. Consequently, research on prediction of human mobility has drawn significant attention in the last decade. Employing information-theoretic ... More

Securing Voice-driven Interfaces against Fake (Cloned) Audio AttacksFeb 18 2019Voice cloning technologies have found applications in a variety of areas ranging from personalized speech interfaces to advertisement, robotics, and so on. Existing voice cloning systems are capable of learning speaker characteristics and use trained ... More

Robot Co-design: Beyond the Monotone CaseFeb 15 2019Recent advances in 3D printing and manufacturing of miniaturized robotic hardware and computing are paving the way to build inexpensive and disposable robots. This will have a large impact on several applications including scientific discovery (e.g., ... More

Hyperbox based machine learning algorithms: A comprehensive surveyJan 31 2019Feb 04 2019With the rapid development of digital information, the data volume generated by humans and machines is growing exponentially. Along with this trend, machine learning algorithms have been formed and evolved continuously to discover new information and ... More

Hyperbox based machine learning algorithms: A comprehensive surveyJan 31 2019Mar 22 2019With the rapid development of digital information, the data volume generated by humans and machines is growing exponentially. Along with this trend, machine learning algorithms have been formed and evolved continuously to discover new information and ... More

Error Feedback Fixes SignSGD and other Gradient Compression SchemesJan 28 2019Sign-based algorithms (e.g. signSGD) have been proposed as a biased gradient compression technique to alleviate the communication bottleneck in training large neural networks across multiple workers. We show simple convex counter-examples where signSGD ... More

The CM Algorithm for the Maximum Mutual Information Classifications of Unseen InstancesJan 28 2019The Maximum Mutual Information (MMI) criterion is different from the Least Error Rate (LER) criterion. It can reduce failing to report small probability events. This paper introduces the Channels Matching (CM) algorithm for the MMI classifications of ... More

Plantinga-Vegter algorithm takes average polynomial timeJan 26 2019We exhibit a condition-based analysis of the adaptive subdivision algorithm due to Plantinga and Vegter. The first complexity analysis of the PV Algorithm is due to Burr, Gao and Tsigaridas who proved a $O\big(2^{\tau d^{4}\log d}\big)$ worst-case cost ... More

Plantinga-Vegter algorithm takes average polynomial timeJan 26 2019Apr 18 2019We exhibit a condition-based analysis of the adaptive subdivision algorithm due to Plantinga and Vegter. The first complexity analysis of the PV Algorithm is due to Burr, Gao and Tsigaridas who proved a $O\big(2^{\tau d^{4}\log d}\big)$ worst-case cost ... More

Embedding quadratization gadgets on Chimera and Pegasus graphsJan 23 2019We group all known quadratizations of cubic and quartic terms in binary optimization problems into six and seven unique graphs respectively. We then perform a minor embedding of these graphs onto the well-known Chimera graph, and the brand new Pegasus ... More

Pegasus: The second connectivity graph for large-scale quantum annealing hardwareJan 22 2019Pegasus is a graph which offers substantially increased connectivity between the qubits of quantum annealing hardware compared to the graph Chimera. It is the first fundamental change in the connectivity graph of quantum annealers built by D-Wave since ... More

Quadratization in discrete optimization and quantum mechanicsJan 14 2019A book about turning high-degree optimization problems into quadratic optimization problems that maintain the same global minimum (ground state). This book explores quadratizations for pseudo-Boolean optimization, perturbative gadgets used in QMA completeness ... More

The Deeper, the Better: Analysis of Person Attributes RecognitionJan 11 2019In person attributes recognition, we describe a person in terms of their appearance. Typically, this includes a wide range of traits including age, gender, clothing, and footwear. Although this could be used in a wide variety of scenarios, it generally ... More

Responsive Equilibrium for Self-Adaptive Ubiquitous InteractionDec 31 2018This work attempts to unify two domains: the Game Theory for cooperative control systems and the Responsive Web Design, under the umbrella of crowdsourcing for information gain on Ubiquous Sytems related to different devices (as PC, Tablet, Mobile,...) ... More

Nonlinear Robust Filtering of Sampled-Data Dynamical SystemsDec 23 2018This work is concerned with robust filtering of nonlinear sampled-data systems with and without exact discrete-time models. A linear matrix inequality (LMI) based approach is proposed for the design of robust $H_{\infty}$ observers for a class of Lipschitz ... More

Interest-Aware Delivery for Mobile Social Networks: A TRACE-driven ApproachDec 16 2018We envision future mobile networks to be human-centric supporting interest-aware delivery, where an interest maybe based on behavior, such as mobility pattern, location, or web browsing (or user profile) such as affiliation, attributes, or activity. An ... More

Simulation to Scaled City: Zero-Shot Policy Transfer for Traffic Control via Autonomous VehiclesDec 14 2018Feb 22 2019Using deep reinforcement learning, we train control policies for autonomous vehicles leading a platoon of vehicles onto a roundabout. Using Flow, a library for deep reinforcement learning in micro-simulators, we train two policies, one policy with noise ... More

Simulation to scaled city: zero-shot policy transfer for traffic control via autonomous vehiclesDec 14 2018Using deep reinforcement learning, we train control policies for autonomous vehicles leading a platoon of vehicles onto a roundabout. Using Flow, a library for deep reinforcement learning in micro-simulators, we train two policies, one policy with noise ... More

On balanced clustering with tree-like structures over clustersDec 09 2018The article addresses balanced clustering problems with an additional requirement as a tree-like structure over the obtained balanced clusters. This kind of clustering problems can be useful in some applications (e.g., network design, management and routing). ... More

A note on solving nonlinear optimization problems in variable precisionDec 09 2018Dec 11 2018This short note considers an efficient variant of the trust-region algorithm with dynamic accuracy proposed Carter (1993) and Conn, Gould and Toint (2000) as a tool for very high-performance computing, an area where it is critical to allow multi-precision ... More

A note on solving nonlinear optimization problems in variable precisionDec 09 2018Apr 12 2019This short note considers an efficient variant of the trust-region algorithm with dynamic accuracy proposed Carter (1993) and Conn, Gould and Toint (2000) as a tool for very high-performance computing, an area where it is critical to allow multi-precision ... More

Naive Dictionary On Musical Corpora: From Knowledge Representation To Pattern RecognitionNov 29 2018In this paper, we propose and develop the novel idea of treating musical sheets as literary documents in the traditional text analytics parlance, to fully benefit from the vast amount of research already existing in statistical text mining and topic modelling. ... More

Wearable affect and stress recognition: A reviewNov 21 2018Affect recognition aims to detect a person's affective state based on observables, with the goal to e.g. provide reasoning for decision making or support mental wellbeing. Recently, besides approaches based on audio, visual or text information, solutions ... More

The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecastsNov 21 2018We propose a multivariate elastic net regression forecast model for German quarter-hourly electricity spot markets. While the literature is diverse on day-ahead prediction approaches, both the intraday continuous and intraday call-auction prices have ... More

OrthoSeg: A Deep Multimodal Convolutional Neural Network for Semantic Segmentation of OrthoimageryNov 19 2018Nov 20 2018This paper addresses the task of semantic segmentation of orthoimagery using multimodal data e.g. optical RGB, infrared and digital surface model. We propose a deep convolutional neural network architecture termed OrthoSeg for semantic segmentation using ... More

Cross-modality deep learning brings bright-field microscopy contrast to holographyNov 17 2018Deep learning brings bright-field microscopy contrast to holographic images of a sample volume, bridging the volumetric imaging capability of holography with the speckle- and artifact-free image contrast of bright-field incoherent microscopy.

Jointly Learning to Label Sentences and TokensNov 14 2018Learning to construct text representations in end-to-end systems can be difficult, as natural languages are highly compositional and task-specific annotated datasets are often limited in size. Methods for directly supervising language composition can ... More

Deep BV: A Fully Automated System for Brain Ventricle Localization and Segmentation in 3D Ultrasound Images of Embryonic MiceNov 05 2018Volumetric analysis of brain ventricle (BV) structure is a key tool in the study of central nervous system development in embryonic mice. High-frequency ultrasound (HFU) is the only non-invasive, real-time modality available for rapid volumetric imaging ... More

From the EM Algorithm to the CM-EM Algorithm for Global Convergence of Mixture ModelsOct 26 2018The Expectation-Maximization (EM) algorithm for mixture models often results in slow or invalid convergence. The popular convergence proof affirms that the likelihood increases with Q; Q is increasing in the M -step and non-decreasing in the E-step. The ... More

An $O(1/\varepsilon)$-Iteration Triangle Algorithm for A Convex Hull MembershipOct 17 2018A fundamental problem in linear programming, machine learning, and computational geometry is the {\it Convex Hull Membership} (CHM): Given a point $p$ and a subset $S$ of $n$ points in $\mathbb{R}^m$, is $p \in conv(S)$? The {\it Triangle Algorithm} (TA) ... More

Spherical Triangle Algorithm: A Fast Oracle for Convex Hull Membership QueriesOct 17 2018Apr 05 2019The it Convex Hull Membership(CHM) problem is: Given a point $p$ and a subset $S$ of $n$ points in $\mathbb{R}^m$, is $p \in conv(S)$? CHM is not only a fundamental problem in Linear Programming, Computational Geometry, Machine Learning and Statistics, ... More

Hyper-Process Model: A Zero-Shot Learning algorithm for Regression Problems based on Shape AnalysisOct 16 2018Zero-shot learning (ZSL) can be defined by correctly solving a task where no training data is available, based on previous acquired knowledge from different, but related tasks. So far, this area has mostly drawn the attention from computer vision community ... More

Deep learning-based super-resolution in coherent imaging systemsOct 15 2018We present a deep learning framework based on a generative adversarial network (GAN) to perform super-resolution in coherent imaging systems. We demonstrate that this framework can enhance the resolution of both pixel size-limited and diffraction-limited ... More

Multi-scale Geometric Summaries for Similarity-based Sensor FusionOct 13 2018Jan 05 2019In this work, we address fusion of heterogeneous sensor data using wavelet-based summaries of fused self-similarity information from each sensor. The technique we develop is quite general, does not require domain specific knowledge or physical models, ... More

A Practical Approach to Sizing Neural NetworksOct 04 2018Memorization is worst-case generalization. Based on MacKay's information theoretic model of supervised machine learning, this article discusses how to practically estimate the maximum size of a neural network given a training data set. First, we present ... More

Accelerated PDE's for efficient solution of regularized inversion problemsSep 30 2018We further develop a new framework, called PDE Acceleration, by applying it to calculus of variations problems defined for general functions on $\mathbb{R}^n$, obtaining efficient numerical algorithms to solve the resulting class of optimization problems ... More

MIDI-VAE: Modeling Dynamics and Instrumentation of Music with Applications to Style TransferSep 20 2018We introduce MIDI-VAE, a neural network model based on Variational Autoencoders that is capable of handling polyphonic music with multiple instrument tracks, as well as modeling the dynamics of music by incorporating note durations and velocities. We ... More

Symbolic Music Genre Transfer with CycleGANSep 20 2018Deep generative models such as Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) have recently been applied to style and domain transfer for images, and in the case of VAEs, music. GAN-based models employing several generators ... More

Twisty Takens: A Geometric Characterization of Good Observations on Dense TrajectoriesSep 19 2018May 05 2019In nonlinear time series analysis and dynamical systems theory, Takens' embedding theorem states that the sliding window embedding of a generic observation along trajectories in a state space, recovers the region traversed by the dynamics. This can be ... More

Twisty Takens: A Geometric Characterization of Good Observations on Dense TrajectoriesSep 19 2018Oct 03 2018In nonlinear time series analysis and dynamical systems theory, Takens' embedding theorem states that the sliding window embedding of a generic observation along trajectories in a state space, recovers the region traversed by the dynamics. This can be ... More

Fair lending needs explainable models for responsible recommendationSep 12 2018The financial services industry has unique explainability and fairness challenges arising from compliance and ethical considerations in credit decisioning. These challenges complicate the use of model machine learning and artificial intelligence methods ... More

From Bayesian Inference to Logical Bayesian Inference: A New Mathematical Frame for Semantic Communication and Machine LearningSep 03 2018Bayesian Inference (BI) uses the Bayes' posterior whereas Logical Bayesian Inference (LBI) uses the truth function or membership function as the inference tool. LBI was proposed because BI was not compatible with the classical Bayes' prediction and didn't ... More

Statistical Analysis Driven Optimized Deep Learning System for Intrusion DetectionAug 16 2018Attackers have developed ever more sophisticated and intelligent ways to hack information and communication technology systems. The extent of damage an individual hacker can carry out upon infiltrating a system is well understood. A potentially catastrophic ... More

Computer Modeling of Personal Autonomy and Legal EquilibriumAug 16 2018Empirical studies of personal autonomy as state and status of individual freedom, security, and capacity to control own life, particularly by independent legal reasoning, are need dependable models and methods of precise computation. Three simple models ... More

On the Relation Between Mobile Encounters and Web Traffic Patterns: A Data-driven StudyAug 11 2018Nov 05 2018Mobility and network traffic have been traditionally studied separately. Their interaction is vital for generations of future mobile services and effective caching, but has not been studied in depth with real-world big data. In this paper, we characterize ... More

Adapting website design for people with color-blindnessAug 05 2018The aim of the study is the description of problem of developing web design for people with color blindness. The objectives of the study are familiarising with the exiting algorithms of simulation color blindness and searching the most appropriate color ... More

On Disjoint Holes in Point SetsJul 27 2018Nov 14 2018Given a set of points $S \subseteq \mathbb{R}^2$, a subset $X \subseteq S$, $|X|=k$, is called $k$-gon if all points of $X$ lie on the boundary of the convex hull $\mathrm{conv} (X)$, and $k$-hole if, in addition, no point of $S \setminus X$ lies in $\mathrm{conv} ... More

On Disjoint Holes in Point SetsJul 27 2018Feb 25 2019Given a set of points $S \subseteq \mathbb{R}^2$, a subset $X \subseteq S$, $|X|=k$, is called $k$-gon if all points of $X$ lie on the boundary of the convex hull $\mathrm{conv} (X)$, and $k$-hole if, in addition, no point of $S \setminus X$ lies in $\mathrm{conv} ... More

Using technology of augmented reality in a mobile-based learning environment of the higher educational institutionJul 23 2018The definition of the augmented reality concept is based on the analysis of scientific publications. It is noted that online experiments with augmented reality provide students with the opportunity to observe and describe the operation with real systems ... More

The Bottleneck Simulator: A Model-based Deep Reinforcement Learning ApproachJul 12 2018Deep reinforcement learning has recently shown many impressive successes. However, one major obstacle towards applying such methods to real-world problems is their lack of data-efficiency. To this end, we propose the Bottleneck Simulator: a model-based ... More

CoCalc as a Learning Tool for Neural Network Simulation in the Special Course "Foundations of Mathematic Informatics"Jul 02 2018The role of neural network modeling in the learning content of the special course "Foundations of Mathematical Informatics" was discussed. The course was developed for the students of technical universities - future IT-specialists and directed to breaking ... More

Log Skeletons: A Classification Approach to Process DiscoveryJun 21 2018To test the effectiveness of process discovery algorithms, a Process Discovery Contest (PDC) has been set up. This PDC uses a classification approach to measure this effectiveness: The better the discovered model can classify whether or not a new trace ... More

Expanding the Active Inference Landscape: More Intrinsic Motivations in the Perception-Action LoopJun 21 2018Active inference is an ambitious theory that treats perception, inference and action selection of autonomous agents under the heading of a single principle. It suggests biologically plausible explanations for many cognitive phenomena, including consciousness. ... More

Coupled Fluid Density and Motion from Single ViewsJun 18 2018We present a novel method to reconstruct a fluid's 3D density and motion based on just a single sequence of images. This is rendered possible by using powerful physical priors for this strongly under-determined problem. More specifically, we propose a ... More

NumtaDB - Assembled Bengali Handwritten DigitsJun 06 2018To benchmark Bengali digit recognition algorithms, a large publicly available dataset is required which is free from biases originating from geographical location, gender, and age. With this aim in mind, NumtaDB, a dataset consisting of more than 85,000 ... More

Deep Bayesian regression modelsJun 06 2018Jun 07 2018Regression models are used for inference and prediction in a wide range of applications providing a powerful scientific tool for researchers and analysts from different fields. In many research fields the amount of available data as well as the number ... More

Optimal Clustering under UncertaintyJun 02 2018Classical clustering algorithms typically either lack an underlying probability framework to make them predictive or focus on parameter estimation rather than defining and minimizing a notion of error. Recent work addresses these issues by developing ... More

Electronic schematic for bio-plausible dopamine neuromodulation of eSTDP and iSTDPMay 28 2018In this technical report we present novel results of the dopamine bio-plausible neuromodulation excitatory (eSTDP) and inhibitory (iSTDP) learning. We present the principal schematic for the neuromodulation of D1 and D2 receptors of dopamine, wiring schematic ... More

Body and Tail - Separating the distribution function by an efficient tail-detecting procedure in risk managementMay 25 2018In risk management, tail risks are of crucial importance. The quality of a tail model, which is determined by data from an unknown distribution, depends critically on the subset of data used to model the tail. Based on a suitably weighted mean square ... More

Learning to Propagate Labels: Transductive Propagation Network for Few-shot LearningMay 25 2018Feb 08 2019The goal of few-shot learning is to learn a classifier that generalizes well even when trained with a limited number of training instances per class. The recently introduced meta-learning approaches tackle this problem by learning a generic classifier ... More

WSD algorithm based on a new method of vector-word contexts proximity calculation via epsilon-filtrationMay 24 2018Jun 18 2018The problem of word sense disambiguation (WSD) is considered in the article. Given a set of synonyms (synsets) and sentences with these synonyms. It is necessary to select the meaning of the word in the sentence automatically. 1285 sentences were tagged ... More

Scoring Lexical Entailment with a Supervised Directional Similarity NetworkMay 23 2018We present the Supervised Directional Similarity Network (SDSN), a novel neural architecture for learning task-specific transformation functions on top of general-purpose word embeddings. Relying on only a limited amount of supervision from task-specific ... More

Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworksMay 17 2018We conduct an extensive empirical study on short-term electricity price forecasting (EPF) to address the long-standing question if the optimal model structure for EPF is univariate or multivariate. We provide evidence that despite a minor edge in predictive ... More

Topological Eulerian Synthesis of Slow Motion Periodic VideosMay 15 2018We consider the problem of taking a video that is comprised of multiple periods of repetitive motion, and reordering the frames of the video into a single period, producing a detailed, single cycle video of motion. This problem is challenging, as such ... More

Zero-shot Sequence Labeling: Transferring Knowledge from Sentences to TokensMay 06 2018Can attention- or gradient-based visualization techniques be used to infer token-level labels for binary sequence tagging problems, using networks trained only on sentence-level labels? We construct a neural network architecture based on soft attention, ... More

Pauling entropy, metastability and equilibrium in Dy$_2$Ti$_2$O$_7$ spin iceApr 24 2018Determining the fate of the Pauling entropy in the classical spin ice material Dy$_2$Ti$_2$O$_7$ with respect to the third law of thermodynamics has become an important test case for understanding the existence and stability of ice-rule states in general. ... More

Modelling Bitcoin in AgdaApr 17 2018We present two models of the block chain of Bitcoin in the interactive theorem prover Agda. The first one is based on a simple model of bank accounts, while having transactions with multiple inputs and outputs. The second model models transactions, which ... More

Simon's Anthill: Mapping and Navigating Belief SpacesApr 15 2018In the parable of Simon's Ant, an ant follows a complex path along a beach on to reach its goal. The story shows how the interaction of simple rules and a complex environment result in complex behavior. But this relationship can be looked at in another ... More

This One Simple Trick Disrupts Digital CommunitiesApr 06 2018Jun 26 2018This paper describes an agent based simulation used to model human actions in belief space, a high-dimensional subset of information space associated with opinions. Using insights from animal collective behavior, we are able to simulate and identify behavior ... More

QuipuNet: convolutional neural network for single-molecule nanopore sensingMar 27 2018May 29 2018Nanopore sensing is a versatile technique for the analysis of molecules on the single-molecule level. However, extracting information from data with established algorithms usually requires time-consuming checks by an experienced researcher due to inherent ... More

3D Reconstruction & Assessment Framework based on affordable 2D LidarMar 24 2018Sep 10 2018Lidar is extensively used in the industry and mass-market. Due to its measurement accuracy and insensitivity to illumination compared to cameras, It is applied onto a broad range of applications, like geodetic engineering, self driving cars or virtual ... More

Socio-spatial Self-organizing Maps: Using Social Media to Assess Relevant Geographies for Exposure to Social ProcessesMar 23 2018Sep 04 2018Social media offers a unique window into attitudes like racism and homophobia, exposure to which are important, hard to measure and understudied social determinants of health. However, individual geo-located observations from social media are noisy and ... More

Extended depth-of-field in holographic image reconstruction using deep learning based auto-focusing and phase-recoveryMar 21 2018Holography encodes the three dimensional (3D) information of a sample in the form of an intensity-only recording. However, to decode the original sample image from its hologram(s), auto-focusing and phase-recovery are needed, which are in general cumbersome ... More

Calculated attributes of synonym setsMar 05 2018The goal of formalization, proposed in this paper, is to bring together, as near as possible, the theoretic linguistic problem of synonym conception and the computer linguistic methods based generally on empirical intuitive unjustified factors. Using ... More

Rederiving the Upper Bound for Halving Edges using Cardano's FormulaFeb 11 2018In this paper we rederive an old upper bound on the number of halving edges present in the halving graph of an arbitrary set of $n$ points in 2-dimensions which are placed in general position. We provide a different analysis of an identity discovered ... More

Multiparametric Deep Learning Tissue Signatures for a Radiological Biomarker of Breast Cancer: Preliminary ResultsFeb 10 2018A new paradigm is beginning to emerge in Radiology with the advent of increased computational capabilities and algorithms. This has led to the ability of real time learning by computer systems of different lesion types to help the radiologist in defining ... More

Biological Mechanisms for Learning: A Computational Model of Olfactory Learning in the Manduca sexta Moth, with Applications to Neural NetsFeb 08 2018The insect olfactory system, which includes the antennal lobe (AL), mushroom body (MB), and ancillary structures, is a relatively simple neural system capable of learning. Its structural features, which are widespread in biological neural systems, process ... More