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Semiparametric Wavelet-based JPEG IV Estimator for endogenously truncated dataAug 06 2019A new and an enriched JPEG algorithm is provided for identifying redundancies in a sequence of irregular noisy data points which also accommodates a reference-free criterion function. Our main contribution is by formulating analytically (instead of approximating) ... More
Augmenting Music Sheets with Harmonic FingerprintsJul 31 2019Conventional Music Notation (CMN) is the well-established foundation for the written communication of musical information, such as rhythm, harmony, or timbre. However, CMN suffers from the complexity of its visual encoding and the need for extensive training ... More
A comparative study of general fuzzy min-max neural networks for pattern classification problemsJul 31 2019General fuzzy min-max (GFMM) neural network is a generalization of fuzzy neural networks formed by hyperbox fuzzy sets for classification and clustering problems. Two principle algorithms are deployed to train this type of neural network, i.e., incremental ... More
A feasibility study of deep neural networks for the recognition of banknotes regarding central bank requirementsJul 18 2019This paper contains a feasibility study of deep neural networks for the classification of Euro banknotes with respect to requirements of central banks on the ATM and high speed sorting industry. Instead of concentrating on the accuracy for a large number ... More
Deep learning-based color holographic microscopyJul 15 2019We report a framework based on a generative adversarial network (GAN) that performs high-fidelity color image reconstruction using a single hologram of a sample that is illuminated simultaneously by light at three different wavelengths. The trained network ... More
Quick, Stat!: A Statistical Analysis of the Quick, Draw! DatasetJul 15 2019The Quick, Draw! Dataset is a Google dataset with a collection of 50 million drawings, divided in 345 categories, collected from the users of the game Quick, Draw!. In contrast with most of the existing image datasets, in the Quick, Draw! Dataset, drawings ... More
Discontinuous Galerkin discretization for two-equation turbulence closure modelJul 10 2019Accurate representation of vertical turbulence is crucial for numerical ocean modelling, both in global and coastal applications. The state-of-the-art approach is to use two-equation turbulence closure models which introduces two dynamic equations to ... More
Applications of a Novel Knowledge Discovery and Data Mining Process Model for MetabolomicsJul 09 2019Jul 30 2019This work demonstrates the execution of a novel process model for knowledge discovery and data mining for metabolomics (MeKDDaM). It aims to illustrate MeKDDaM process model applicability using four different real-world applications and to highlight its ... More
Applications of a Novel Knowledge Discovery and Data Mining Process Model for MetabolomicsJul 09 2019This work demonstrates the execution of a novel process model for knowledge discovery and data mining for metabolomics (MeKDDaM). It aims to illustrate MeKDDaM process model applicability using four different real-world applications and to highlight its ... More
Computer-Aided Data Mining: Automating a Novel Knowledge Discovery and Data Mining Process Model for MetabolomicsJul 09 2019This work presents MeKDDaM-SAGA, computer-aided automation software for implementing a novel knowledge discovery and data mining process model that was designed for performing justifiable, traceable and reproducible metabolomics data analysis. The process ... More
Adaptive Music Composition for GamesJul 02 2019The generation of music that adapts dynamically to content and actions has an important role in building more immersive, memorable and emotive game experiences. To date, the development of adaptive music systems for video games is limited by both the ... More
A Winograd-based Integrated Photonics Accelerator for Convolutional Neural NetworksJun 25 2019Neural Networks (NNs) have become the mainstream technology in the artificial intelligence (AI) renaissance over the past decade. Among different types of neural networks, convolutional neural networks (CNNs) have been widely adopted as they have achieved ... More
Gaze-Contingent Ocular Parallax Rendering for Virtual RealityJun 24 2019Immersive computer graphics systems strive to generate perceptually realistic user experiences. Current-generation virtual reality (VR) displays are successful in accurately rendering many perceptually important effects, including perspective, disparity, ... More
Low-dimensional Embodied Semantics for Music and LanguageJun 20 2019Embodied cognition states that semantics is encoded in the brain as firing patterns of neural circuits, which are learned according to the statistical structure of human multimodal experience. However, each human brain is idiosyncratically biased, according ... More
Regional based query in graph active learningJun 20 2019Graph convolution networks (GCN) have emerged as the leading method to classify node classes in networks, and have reached the highest accuracy in multiple node classification tasks. In the absence of available tagged samples, active learning methods ... More
Empowering swarm-based optimizers by multi-scale search to enhance Gradient Descent initialization performanceJun 13 2019Swarm-based optimizers like Particle Swarm Optimization or Imperialistic Competitive Algorithm that act under influences of cooperation or competition among groups, are unable to search in multiple volumes of locality or globality and do not have nested ... More
Visual Wake Words DatasetJun 12 2019The emergence of Internet of Things (IoT) applications requires intelligence on the edge. Microcontrollers provide a low-cost compute platform to deploy intelligent IoT applications using machine learning at scale, but have extremely limited on-chip memory ... More
Weighted Quasi Interpolant Spline Approximation of 3D point clouds via local refinementJun 10 2019We present a new surface approximation, the Weighted Quasi Interpolant Spline Approximation (w-QISA), to approximate very large and noisy point clouds. We adopt local implicit representations based on three key ingredients: 1) a local mesh for the piecewise ... More
Global Semantic Description of Objects based on Prototype TheoryJun 08 2019In this paper, we introduce a novel semantic description approach inspired on Prototype Theory foundations. We propose a Computational Prototype Model (CPM) that encodes and stores the central semantic meaning of objects category: the semantic prototype. ... More
Kinetic Market Model: An Evolutionary AlgorithmJun 04 2019This research proposes the econophysics kinetic market model as an evolutionary algorithm's instance. The immediate results from this proposal is a new replacement rule for family competition genetic algorithms. It also represents a starting point to ... More
PowerSGD: Practical Low-Rank Gradient Compression for Distributed OptimizationMay 31 2019We study gradient compression methods to alleviate the communication bottleneck in data-parallel distributed optimization. Despite the significant attention received, current compression schemes either do not scale well or fail to achieve the target test ... More
Bandlimiting Neural Networks Against Adversarial AttacksMay 30 2019In this paper, we study the adversarial attack and defence problem in deep learning from the perspective of Fourier analysis. We first explicitly compute the Fourier transform of deep ReLU neural networks and show that there exist decaying but non-zero ... More
Clustering without Over-RepresentationMay 29 2019In this paper we consider clustering problems in which each point is endowed with a color. The goal is to cluster the points to minimize the classical clustering cost but with the additional constraint that no color is over-represented in any cluster. ... More
A Quaternion-based Certifiably Optimal Solution to the Wahba Problem with OutliersMay 29 2019Jul 23 2019The Wahba problem, also known as rotation search, seeks to find the best rotation to align two sets of vector observations given putative correspondences, and is a fundamental routine in many computer vision and robotics applications. This work proposes ... More
A Quaternion-based Certifiably Optimal Solution to the Wahba Problem with OutliersMay 29 2019Aug 16 2019The Wahba problem, also known as rotation search, seeks to find the best rotation to align two sets of vector observations given putative correspondences, and is a fundamental routine in many computer vision and robotics applications. This work proposes ... More
A Quaternion-based Certifiably Optimal Solution to the Wahba Problem with OutliersMay 29 2019The Wahba problem, also known as rotation search, seeks to find the best rotation to align two sets of vector observations given putative correspondences, and is a fundamental routine in many computer vision and robotics applications. This work proposes ... More
An Effective Multi-Resolution Hierarchical Granular Representation based Classifier using General Fuzzy Min-Max Neural NetworkMay 29 2019Jun 03 2019Motivated by the practical demands for simplification of data towards being consistent with human thinking and problem solving as well as tolerance of uncertainty, information granules are becoming important entities in data processing at different levels ... More
An Effective Multi-Resolution Hierarchical Granular Representation based Classifier using General Fuzzy Min-Max Neural NetworkMay 29 2019Motivated by the practical demands for simplification of data towards being consistent with human thinking and problem solving as well as tolerance of uncertainty, information granules are becoming important entities in data processing at different levels ... More
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 2019Jun 12 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
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 2019Jun 27 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
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
Computer Science and Metaphysics: A Cross-FertilizationMay 01 2019Jun 15 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
Computer Science and Metaphysics: A Cross-FertilizationMay 01 2019Aug 11 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
Deep Learning for Audio Signal ProcessingApr 30 2019May 25 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 2019Jul 09 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 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 Polynomial-time Solution for Robust Registration with Extreme Outlier RatesMar 20 2019Jun 30 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
Combining Model and Parameter Uncertainty in Bayesian Neural NetworksMar 18 2019May 25 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
Analyzing Input and Output Representations for Speech-Driven Gesture GenerationMar 08 2019Jun 11 2019This paper presents a novel framework for automatic speech-driven gesture generation, applicable to human-agent interaction including both virtual agents and robots. Specifically, we extend recent deep-learning-based, data-driven methods for speech-driven ... 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
Error Feedback Fixes SignSGD and other Gradient Compression SchemesJan 28 2019May 29 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