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09/12/2023
The Relational Bottleneck as an Inductive Bias for Efficient Abstraction
A central challenge for cognitive science is to explain how abstract con...
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04/01/2023
Abstractors: Transformer Modules for Symbolic Message Passing and Relational Reasoning
A framework is proposed that casts relational learning in terms of trans...
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02/21/2023
From seeing to remembering: Images with harder-to-reconstruct representations leave stronger memory traces
Much of what we remember is not due to intentional selection, but simply...
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05/26/2022
Emergent organization of receptive fields in networks of excitatory and inhibitory neurons
Local patterns of excitation and inhibition that can generate neural wav...
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06/10/2021
Convergence and Alignment of Gradient Descent with Random Back Propagation Weights
Stochastic gradient descent with backpropagation is the workhorse of art...
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06/26/2020
The huge Package for High-dimensional Undirected Graph Estimation in R
We describe an R package named huge which provides easy-to-use functions...
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05/20/2020
Model Repair: Robust Recovery of Over-Parameterized Statistical Models
A new type of robust estimation problem is introduced where the goal is ...
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07/19/2019
Surfing: Iterative optimization over incrementally trained deep networks
We investigate a sequential optimization procedure to minimize the empir...
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07/19/2019
Fair quantile regression
Quantile regression is a tool for learning conditional distributions. In...
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02/16/2019
TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts
Scientific documents rely on both mathematics and text to communicate id...
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05/16/2018
Prediction Rule Reshaping
Two methods are proposed for high-dimensional shape-constrained regressi...
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03/04/2018
Distributed Nonparametric Regression under Communication Constraints
This paper studies the problem of nonparametric estimation of a smooth f...
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10/02/2017
Testing for Global Network Structure Using Small Subgraph Statistics
We study the problem of testing for community structure in networks usin...
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05/24/2016
Local Minimax Complexity of Stochastic Convex Optimization
We extend the traditional worst-case, minimax analysis of stochastic con...
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05/23/2016
Convergence Analysis for Rectangular Matrix Completion Using Burer-Monteiro Factorization and Gradient Descent
We address the rectangular matrix completion problem by lifting the unkn...
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06/19/2015
A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements
We propose a simple, scalable, and fast gradient descent algorithm to op...
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03/25/2015
Quantized Nonparametric Estimation over Sobolev Ellipsoids
We formulate the notion of minimax estimation under storage or communica...
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11/07/2014
Faithful Variable Screening for High-Dimensional Convex Regression
We study the problem of variable selection in convex nonparametric regre...
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09/24/2014
Quantized Estimation of Gaussian Sequence Models in Euclidean Balls
A central result in statistical theory is Pinsker's theorem, which chara...
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01/10/2013
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk
We present an iterative Markov chainMonte Carlo algorithm for computingr...
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01/09/2013
Nonparametric Reduced Rank Regression
We propose an approach to multivariate nonparametric regression that gen...
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12/12/2012
Expectation-Propogation for the Generative Aspect Model
The generative aspect model is an extension of the multinomial model for...
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07/11/2012
Variational Chernoff Bounds for Graphical Models
Recent research has made significant progress on the problem of bounding...
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06/27/2012
The Nonparanormal SKEPTIC
We propose a semiparametric approach, named nonparanormal skeptic, for e...
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06/27/2012
Conditional Sparse Coding and Grouped Multivariate Regression
We study the problem of multivariate regression where the data are natur...
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06/18/2012
Sparse Additive Functional and Kernel CCA
Canonical Correlation Analysis (CCA) is a classical tool for finding cor...
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02/10/2012
High Dimensional Semiparametric Gaussian Copula Graphical Models
In this paper, we propose a semiparametric approach, named nonparanormal...
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01/04/2012
Sparse Nonparametric Graphical Models
We present some nonparametric methods for graphical modeling. In the dis...
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08/31/2010
Union Support Recovery in Multi-task Learning
We sharply characterize the performance of different penalization scheme...
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01/10/2010
Forest Density Estimation
We study graph estimation and density estimation in high dimensions, usi...
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02/20/2008
Time Varying Undirected Graphs
Undirected graphs are often used to describe high dimensional distributi...
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06/04/2007