Papers
5,893 papers found
Bayesian latent structure discovery from multi-neuron recordings
Scott Linderman, Ryan P. Adams, Jonathan W Pillow
Stochastic Structured Prediction under Bandit Feedback
Artem Sokolov, Julia Kreutzer, Stefan Riezler et al.
Composing graphical models with neural networks for structured representations and fast inference
Matthew J Johnson, David K. Duvenaud, Alex Wiltschko et al.
Structured Matrix Recovery via the Generalized Dantzig Selector
Sheng Chen, Arindam Banerjee
Tree-Structured Reinforcement Learning for Sequential Object Localization
Zequn Jie, Xiaodan Liang, Jiashi Feng et al.
A Consistent Regularization Approach for Structured Prediction
Carlo Ciliberto, Lorenzo Rosasco, Alessandro Rudi
Near-Optimal Smoothing of Structured Conditional Probability Matrices
Moein Falahatgar, Mesrob I Ohannessian, Alon Orlitsky
Structured Sparse Regression via Greedy Hard Thresholding
Prateek Jain, Nikhil Rao, Inderjit S Dhillon
A Bio-inspired Redundant Sensing Architecture
Anh Tuan Nguyen, Jian Xu, Zhi Yang
Unified Methods for Exploiting Piecewise Linear Structure in Convex Optimization
Tyler B Johnson, Carlos Guestrin
High Dimensional Structured Superposition Models
Qilong Gu, Arindam Banerjee
Linear-Memory and Decomposition-Invariant Linearly Convergent Conditional Gradient Algorithm for Structured Polytopes
Dan Garber, Dan Garber, Ofer Meshi
Unsupervised Risk Estimation Using Only Conditional Independence Structure
Jacob Steinhardt, Percy Liang
Proximal Deep Structured Models
Shenlong Wang, Sanja Fidler, Raquel Urtasun
Learning A Structured Optimal Bipartite Graph for Co-Clustering
Feiping Nie, Xiaoqian Wang, Cheng Deng et al.
Non-parametric Structured Output Networks
Andreas Lehrmann, Leonid Sigal
Estimation of the covariance structure of heavy-tailed distributions
Xiaohan Wei, Stanislav Minsker
Group Additive Structure Identification for Kernel Nonparametric Regression
Chao Pan, Michael Zhu
A Regularized Framework for Sparse and Structured Neural Attention
Vlad Niculae, Mathieu Blondel
On Structured Prediction Theory with Calibrated Convex Surrogate Losses
Anton Osokin, Francis Bach, Simon Lacoste-Julien
Continuous DR-submodular Maximization: Structure and Algorithms
An Bian, Kfir Levy, Andreas Krause et al.
Learning Causal Structures Using Regression Invariance
AmirEmad Ghassami, Saber Salehkaleybar, Negar Kiyavash et al.
Stochastic Optimization with Variance Reduction for Infinite Datasets with Finite Sum Structure
Alberto Bietti, Julien Mairal
Learning Deep Structured Multi-Scale Features using Attention-Gated CRFs for Contour Prediction
Dan Xu, Wanli Ouyang, Xavier Alameda-Pineda et al.
Gaussian process based nonlinear latent structure discovery in multivariate spike train data
Anqi Wu, Nicholas A. Roy, Stephen Keeley et al.