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Results for "Samira Briongos"
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CacheShield: Protecting Legacy Processes Against Cache AttacksSep 06 2017Cache attacks pose a threat to any code whose execution flow or memory accesses depend on sensitive information. Especially in public clouds, where caches are shared across several tenants, cache attacks remain an unsolved problem. Cache attacks rely ... More Submodular Welfare MaximizationNov 21 2013An overview of different variants of the submodular welfare maximization problem in combinatorial auctions. In particular, I studied the existing algorithmic and game theoretic results for submodular welfare maximization problem and its applications in ... More Clustering and Labelling Auction Fraud DataAug 22 2018Although shill bidding is a common auction fraud, it is however very tough to detect. Due to the unavailability and lack of training data, in this study, we build a high-quality labeled shill bidding dataset based on recently collected auctions from eBay. ... More Properties and use of CMB power spectrum likelihoodsFeb 04 2009Apr 08 2009Fast robust methods for calculating likelihoods from CMB observations on small scales generally rely on approximations based on a set of power spectrum estimators and their covariances. We investigate the optimality of these approximation, how accurate ... More Efficient Local Density Estimation Strategy for VANETsFeb 18 2014Local vehicle density estimation is increasingly becoming an essential factor of many vehicular ad-hoc network applications such as congestion control and traffic state estimation. This estimation is used to get an approximate number of neighbors within ... More Digital Hurewicz Theorem and Digital Homology theoryFeb 06 2019Feb 28 2019In this paper, we develop homology groups for digital images based on cubical singular homology theory for topological spaces. Using this homology, we present digital Hurewicz theorem for the fundamental group of digital images. We also show that the ... More Digital Hurewicz Theorem and Digital Homology theoryFeb 06 2019In this paper, we develop homology groups for digital images based on cubical singular homology theory for topological spaces. Using this homology, we present digital Hurewicz theorem for the fundamental group of digital images. We also show that the ... More Robust Evaluation of Language-Brain Encoding ExperimentsApr 04 2019Language-brain encoding experiments evaluate the ability of language models to predict brain responses elicited by language stimuli. The evaluation scenarios for this task have not yet been standardized which makes it difficult to compare and interpret ... More Usability of Humanly Computable PasswordsDec 11 2017May 24 2018Reusing passwords across multiple websites is a common practice that compromises security. Recently, Blum and Vempala have proposed password strategies to help people calculate, in their heads, passwords for different sites without dependence on third-party ... More Computing all border bases for ideals of pointsJul 07 2017In this paper we consider the problem of computing all possible order ideals and also sets connected to 1, and the corresponding border bases, for the vanishing ideal of a given finite set of points. In this context two different approaches are discussed: ... More Regional Control of Boolean Cellular AutomataJun 16 2016An interesting problem in extended physical systems is that of the regional control, i.e., how to add a suitable control at the boundary or inside a region of interest so that the state of such region is near to a desired one. Many physical problems are ... More Control of cellular automataJun 11 2012We study the problem of master-slave synchronization and control of totalistic cellular automata (CA) by putting a fraction of sites of the slave equal to those of the master and finding the distance between both as a function of this fraction. We present ... More Streaming Verification in Data AnalysisSep 18 2015Streaming interactive proofs (SIPs) are a framework to reason about outsourced computation, where a data owner (the verifier) outsources a computation to the cloud (the prover), but wishes to verify the correctness of the solution provided by the cloud ... More Range Counting Coresets for Uncertain DataApr 15 2013We study coresets for various types of range counting queries on uncertain data. In our model each uncertain point has a probability density describing its location, sometimes defined as k distinct locations. Our goal is to construct a subset of the uncertain ... More RATM: Recurrent Attentive Tracking ModelOct 29 2015Apr 28 2016We present an attention-based modular neural framework for computer vision. The framework uses a soft attention mechanism allowing models to be trained with gradient descent. It consists of three modules: a recurrent attention module controlling where ... More Efficient Decoding of Synchronized Colliding LoRa SignalsFeb 14 2019In LoRa (Long Range), when a collision occurs in the network, each end-device has to retransmit its colliding frame, which reduces the throughput, and increases the energy consumption of the end-devices and the delay of the frames. In this paper, we propose ... More Streaming Verification of Graph PropertiesFeb 26 2016Oct 04 2016Streaming interactive proofs (SIPs) are a framework for outsourced computation. A computationally limited streaming client (the verifier) hands over a large data set to an untrusted server (the prover) in the cloud and the two parties run a protocol to ... More Regional Control of Probabilistic Cellular AutomataJul 11 2018Probabilistic Cellular Automata are extended stochastic systems, widely used for modelling phenomena in many disciplines. The possibility of controlling their behaviour is therefore an important topic. We shall present here an approach to the problem ... More Guarantees for Spectral Clustering with Fairness ConstraintsJan 24 2019Given the widespread popularity of spectral clustering (SC) for partitioning graph data, we study a version of constrained SC in which we try to incorporate the fairness notion proposed by Chierichetti et al. (2017). According to this notion, a clustering ... More Partial Zero-Forcing for Multi-Way Relay NetworksOct 12 2017Apr 19 2018The ever increasing demands for mobile network access have resulted in a significant increase in bandwidth usage. By improving the system spectral efficiency, multi-way relay networks (MWRNs) provide promising approaches to address this challenge. In ... More The Price of Fair PCA: One Extra DimensionOct 31 2018We investigate whether the standard dimensionality reduction technique of PCA inadvertently produces data representations with different fidelity for two different populations. We show on several real-world data sets, PCA has higher reconstruction error ... More An efficient cntfet-based 7-input minority gateMar 09 2013Complementary metal oxide semiconductor technology (CMOS) has been faced critical challenges in nano-scale regime. CNTFET (Carbon Nanotube Field effect transistor) technology is a promising alternative for CMOS technology. In this paper, we proposed a ... More Fair Dimensionality Reduction and Iterative Rounding for SDPsFeb 28 2019We model "fair" dimensionality reduction as an optimization problem. A central example is the fair PCA problem: the input data is divided into $k$ groups, and the goal is to find a single $d$-dimensional representation for all groups for which the maximum ... More Bidirectional Helmholtz MachinesJun 12 2015May 25 2016Efficient unsupervised training and inference in deep generative models remains a challenging problem. One basic approach, called Helmholtz machine, involves training a top-down directed generative model together with a bottom-up auxiliary model used ... More Incremental Reading for Question AnsweringJan 15 2019Any system which performs goal-directed continual learning must not only learn incrementally but process and absorb information incrementally. Such a system also has to understand when its goals have been achieved. In this paper, we consider these issues ... More Towards Deep Conversational RecommendationsDec 18 2018Mar 04 2019There has been growing interest in using neural networks and deep learning techniques to create dialogue systems. Conversational recommendation is an interesting setting for the scientific exploration of dialogue with natural language as the associated ... More FitNets: Hints for Thin Deep NetsDec 19 2014Mar 27 2015While depth tends to improve network performances, it also makes gradient-based training more difficult since deeper networks tend to be more non-linear. The recently proposed knowledge distillation approach is aimed at obtaining small and fast-to-execute ... More FigureQA: An Annotated Figure Dataset for Visual ReasoningOct 19 2017Feb 22 2018We introduce FigureQA, a visual reasoning corpus of over one million question-answer pairs grounded in over 100,000 images. The images are synthetic, scientific-style figures from five classes: line plots, dot-line plots, vertical and horizontal bar graphs, ... More Optimising data for modelling neuronal responsesMay 20 2018In this technical note, we address an unresolved challenge in neuroimaging statistics: how to determine which of several datasets is the best for inferring neuronal responses. Comparisons of this kind are important for experimenters when choosing an imaging ... More Towards Deep Conversational RecommendationsDec 18 2018There has been growing interest in using neural networks and deep learning techniques to create dialogue systems. Conversational recommendation is an interesting setting for the scientific exploration of dialogue with natural language as the associated ... More ChatPainter: Improving Text to Image Generation using DialogueFeb 22 2018Synthesizing realistic images from text descriptions on a dataset like Microsoft Common Objects in Context (MS COCO), where each image can contain several objects, is a challenging task. Prior work has used text captions to generate images. However, captions ... More Adaptive-Latency DRAM (AL-DRAM)Mar 28 2016This paper summarizes the idea of Adaptive-Latency DRAM (AL-DRAM), which was published in HPCA 2015. The key goal of AL-DRAM is to exploit the extra margin that is built into the DRAM timing parameters to reduce DRAM latency. The key observation is that ... More On the Learning Dynamics of Deep Neural NetworksSep 18 2018While a lot of progress has been made in recent years, the dynamics of learning in deep nonlinear neural networks remain to this day largely misunderstood. In this work, we study the case of binary classification and prove various properties of learning ... More Vulnerable to Misinformation? Verifi!Jul 25 2018Mar 17 2019We present Verifi2, a visual analytic system to support the investigation of misinformation on social media. On the one hand, social media platforms empower individuals and organizations by democratizing the sharing of information. On the other hand, ... More Vulnerable to Misinformation? Verifi!Jul 25 2018We present Verifi2, a visual analytic system to support the investigation of misinformation on social media. On the one hand, social media platforms empower individuals and organizations by democratizing the sharing of information. On the other hand, ... More Aharonov-Bohm effect in grapheneNov 09 2007We investigate experimentally transport through ring-shaped devices etched in graphene and observe clear Aharonov-Bohm conductance oscillations. The temperature dependence of the oscillation amplitude indicates that below 1 K the phase coherence length ... More Influence of Ibuprofen on Phospholipid MembranesJun 13 2014Sep 14 2014Basic understanding of biological membranes is of paramount importance as these membranes comprise the very building blocks of life itself. Cells depend in their function on a range of properties of the membrane, which are important for the stability ... More