
Algorithmic Fairness
An increasing number of decisions regarding the daily lives of human bei...
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Private Stochastic Convex Optimization: Optimal Rates in Linear Time
We study differentially private (DP) algorithms for stochastic convex op...
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ExKMC: Expanding Explainable kMeans Clustering
Despite the popularity of explainable AI, there is limited work on effec...
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Lautum Regularization for Semisupervised Transfer Learning
Transfer learning is a very important tool in deep learning as it allows...
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OneGAN: Simultaneous Unsupervised Learning of Conditional Image Generation, Foreground Segmentation, and FineGrained Clustering
We present a method for simultaneously learning, in an unsupervised mann...
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Autoencoders
An autoencoder is a specific type of a neural network, which is mainlyde...
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SampleNet: Differentiable Point Cloud Sampling
There is a growing number of tasks that work directly on point clouds. A...
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Obtaining Faithful Interpretations from Compositional Neural Networks
Neural module networks (NMNs) are a popular approach for modeling compos...
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SuperResolution based on ImageAdapted CNN Denoisers: Incorporating Generalization of Training Data and Internal Learning in Test Time
While deep neural networks exhibit stateoftheart results in the task ...
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Endotracheal Tube Detection and Segmentation in Chest Radiographs using Synthetic Data
Chest radiographs are frequently used to verify the correct intubation o...
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KLT Picker: Particle Picking Using DataDriven Optimal Templates
Particle picking is currently a critical step in the cryoEM single part...
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Single Image Depth Estimation Trained via Depth from Defocus Cues
Estimating depth from a single RGB images is a fundamental task in compu...
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A RotationInvariant Framework for Deep Point Cloud Analysis
Recently, many deep neural networks were designed to process 3D point cl...
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An InformationTheoretic Framework for Nonlinear Canonical Correlation Analysis
Canonical Correlation Analysis (CCA) is a linear representation learning...
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Genetic Network Architecture Search
We propose a method for learning the neural network architecture that ba...
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Specifying Object Attributes and Relations in Interactive Scene Generation
We introduce a method for the generation of images from an input scene g...
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Knee Injury Detection using MRI with EfficientlyLayered Network (ELNet)
Magnetic Resonance Imaging (MRI) is a widelyaccepted imaging technique ...
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Polynomial Tensor Sketch for Elementwise Function of LowRank Matrix
This paper studies how to sketch elementwise functions of lowrank matr...
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Bidirectional OneShot Unsupervised Domain Mapping
We study the problem of mapping between a domain A, in which there is a ...
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Correction Filter for Single Image SuperResolution: Robustifying OfftheShelf Deep SuperResolvers
The single image superresolution task is one of the most examined inver...
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Unsupervised Learning of the Set of Local Maxima
This paper describes a new form of unsupervised learning, whose input is...
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Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering
Answering questions that involve multistep reasoning requires decomposi...
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Memory Augmented Policy Optimization for Program Synthesis with Generalization
This paper presents Memory Augmented Policy Optimization (MAPO): a novel...
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Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors
Deep neural networks (DNNs) are notorious for their vulnerability to adv...
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Disentangling Adaptive Gradient Methods from Learning Rates
We investigate several confounding factors in the evaluation of optimiza...
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Evaluation Metrics for Conditional Image Generation
We present two new metrics for evaluating generative models in the class...
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Explaining Queries over Web Tables to NonExperts
Designing a reliable natural language (NL) interface for querying tables...
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Underwater Single Image Color Restoration Using HazeLines and a New Quantitative Dataset
Underwater images suffer from color distortion and low contrast, because...
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Influence Maximization with Few Simulations
Influence maximization (IM) is the problem of finding a set of s nodes i...
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On the Optimization Dynamics of Wide Hypernetworks
Recent results in the theoretical study of deep learning have shown that...
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Multimodal similaritypreserving hashing
We introduce an efficient computational framework for hashing data belon...
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The Geometric Maximum Traveling Salesman Problem
We consider the traveling salesman problem when the cities are points in...
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Mathematics of Deep Learning
Recently there has been a dramatic increase in the performance of recogn...
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DeepChess: EndtoEnd Deep Neural Network for Automatic Learning in Chess
We present an endtoend learning method for chess, relying on deep neur...
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Neuronlevel Selective Context Aggregation for Scene Segmentation
Contextual information provides important cues for disambiguating visual...
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Should You Derive, Or Let the Data Drive? An Optimization Framework for Hybrid FirstPrinciples DataDriven Modeling
Mathematical models are used extensively for diverse tasks including ana...
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RNN Decoding of Linear Block Codes
Designing a practical, low complexity, close to optimal, channel decoder...
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Image Restoration by Iterative Denoising and Backward Projections
Inverse problems appear in many applications such as image deblurring an...
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Learning to Decode Linear Codes Using Deep Learning
A novel deep learning method for improving the belief propagation algori...
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Tradeoffs between Convergence Speed and Reconstruction Accuracy in Inverse Problems
Solving inverse problems with iterative algorithms is popular, especiall...
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Robust Large Margin Deep Neural Networks
The generalization error of deep neural networks via their classificatio...
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Highdimensional classification by sparse logistic regression
We consider highdimensional binary classification by sparse logistic re...
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On the Stability of Deep Networks
In this work we study the properties of deep neural networks (DNN) with ...
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Experimental Design for NonParametric Correction of Misspecified Dynamical Models
We consider a class of misspecified dynamical models where the governing...
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Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision (Short Version)
Extending the success of deep neural networks to natural language unders...
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Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision
Harnessing the statistical power of neural networks to perform language ...
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Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Deep learning models are often successfully trained using gradient desce...
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Splitting matters: how monotone transformation of predictor variables may improve the predictions of decision tree models
It is widely believed that the prediction accuracy of decision tree mode...
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Machine olfaction using time scattering of sensor multiresolution graphs
In this paper we construct a learning architecture for high dimensional ...
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On Voting and Facility Location
We study mechanisms for candidate selection that seek to minimize the so...
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Tel Aviv University
Tel Aviv University is a public research university in the neighborhood of Ramat Aviv in Tel Aviv, Israel.