
Learn to Expect the Unexpected: Probably Approximately Correct Domain Generalization
Domain generalization is the problem of machine learning when the traini...
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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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Learning to Prune: Speeding up Repeated Computations
It is common to encounter situations where one must solve a sequence of ...
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Causal Feature Discovery through Strategic Modification
We consider an online regression setting in which individuals adapt to t...
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On the Complexity of Minimizing Convex Finite Sums Without Using the Indices of the Individual Functions
Recent advances in randomized incremental methods for minimizing Lsmoot...
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Why do deep convolutional networks generalize so poorly to small image transformations?
Deep convolutional network architectures are often assumed to guarantee ...
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Equal Opportunity in Online Classification with Partial Feedback
We study an online classification problem with partial feedback in which...
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On selfplay computation of equilibrium in poker
We compare performance of the genetic algorithm and the counterfactual r...
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On GANs and GMMs
A longstanding problem in machine learning is to find unsupervised metho...
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Learning Parities with Neural Networks
In recent years we see a rapidly growing line of research which shows le...
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Ballpark Crowdsourcing: The Wisdom of Rough Group Comparisons
Crowdsourcing has become a popular method for collecting labeled trainin...
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On evolutionary selection of blackjack strategies
We apply the approach of evolutionary programming to the problem of opti...
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Benefits of Depth for LongTerm Memory of Recurrent Networks
The key attribute that drives the unprecedented success of modern Recurr...
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SumProductQuotient Networks
We present a novel tractable generative model that extends SumProduct N...
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Neuronlevel Selective Context Aggregation for Scene Segmentation
Contextual information provides important cues for disambiguating visual...
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Gaussian Lower Bound for the Information Bottleneck Limit
The Information Bottleneck (IB) is a conceptual method for extracting th...
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Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions
The driving force behind convolutional networks  the most successful de...
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Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design
Deep convolutional networks have witnessed unprecedented success in vari...
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Optimal Shrinkage of Singular Values Under Random Data Contamination
A low rank matrix X has been contaminated by uniformly distributed noise...
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On the Expressive Power of Overlapping Architectures of Deep Learning
Expressive efficiency refers to the relation between two architectures A...
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Tractable Generative Convolutional Arithmetic Circuits
Casting neural networks in generative frameworks is a highly soughtafte...
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Accelerating Innovation Through Analogy Mining
The availability of large idea repositories (e.g., the U.S. patent datab...
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Inductive Bias of Deep Convolutional Networks through Pooling Geometry
Our formal understanding of the inductive bias that drives the success o...
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Convolutional Rectifier Networks as Generalized Tensor Decompositions
Convolutional rectifier networks, i.e. convolutional neural networks wit...
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Linear Readout of Object Manifolds
Objects are represented in sensory systems by continuous manifolds due t...
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On the Expressive Power of Deep Learning: A Tensor Analysis
It has long been conjectured that hypotheses spaces suitable for data th...
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Deep SimNets
We present a deep layered architecture that generalizes convolutional ne...
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Learning Data Manifolds with a Cutting Plane Method
We consider the problem of classifying data manifolds where each manifol...
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An Axiomatic Approach to Routing
Information delivery in a network of agents is a key issue for large, co...
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Strategyproof Peer Selection using Randomization, Partitioning, and Apportionment
Peer review, evaluation, and selection is a fundamental aspect of modern...
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Covariance Plasticity and Regulated Criticality
We propose that a regulation mechanism based on Hebbian covariance plast...
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InformationTheoretic Bounded Rationality
Bounded rationality, that is, decisionmaking and planning under resourc...
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A Tight Convex Upper Bound on the Likelihood of a Finite Mixture
The likelihood function of a finite mixture model is a nonconvex functi...
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Online Trajectory Segmentation and Summary With Applications to Visualization and Retrieval
Trajectory segmentation is the process of subdividing a trajectory into ...
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Ballpark Learning: Estimating Labels from Rough Group Comparisons
We are interested in estimating individual labels given only coarse, agg...
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Estimating mutual information in high dimensions via classification error
Multivariate pattern analyses approaches in neuroimaging are fundamental...
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How many faces can be recognized? Performance extrapolation for multiclass classification
The difficulty of multiclass classification generally increases with th...
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Memory shapes time perception and intertemporal choices
There is a consensus that human and nonhuman subjects experience tempor...
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Optimized Linear Imputation
Often in realworld datasets, especially in high dimensional data, some ...
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An Algorithm for Training Polynomial Networks
We consider deep neural networks, in which the output of each node is a ...
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LowRank Matrix Recovery from RowandColumn Affine Measurements
We propose and study a rowandcolumn affine measurement scheme for low...
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Predicting Personal Traits from Facial Images using Convolutional Neural Networks Augmented with Facial Landmark Information
We consider the task of predicting various traits of a person given an i...
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Learning Finegrained Features via a CNN Tree for Largescale Classification
We propose a novel approach to enhance the discriminability of Convoluti...
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Efficient coordinatedescent for orthogonal matrices through Givens rotations
Optimizing over the set of orthogonal matrices is a central component in...
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A Quantitative Version of the GibbardSatterthwaite Theorem for Three Alternatives
The GibbardSatterthwaite theorem states that every nondictatorial elec...
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Typical models: minimizing false beliefs
A knowledge system S describing a part of real world does in general not...
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General Deformations of Point Configurations Viewed By a Pinhole Model Camera
This paper is a theoretical study of the following NonRigid Structure f...
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Marginal Likelihoods for Distributed Parameter Estimation of Gaussian Graphical Models
We consider distributed estimation of the inverse covariance matrix, als...
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Learning Sparse LowThreshold Linear Classifiers
We consider the problem of learning a nonnegative linear classifier wit...
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A Cheap System for Vehicle Speed Detection
The reliable detection of speed of moving vehicles is considered key to ...
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Hebrew University of Jerusalem
The Hebrew University of Jerusalem is Israel's secondoldest university, established in 1918, 30 years before the establishment of the State of Israel.