Papers
A hybrid sampler for Poisson-Kingman mixture models
Maria Lomeli, Stefano Favaro, Yee Whye Teh
Algorithmic Stability and Uniform Generalization
Ibrahim M Alabdulmohsin
Algorithms with Logarithmic or Sublinear Regret for Constrained Contextual Bandits
Huasen Wu, R. Srikant, Xin Liu et al.
Alternating Minimization for Regression Problems with Vector-valued Outputs
Prateek Jain, Ambuj Tewari
A Market Framework for Eliciting Private Data
Bo Waggoner, Rafael Frongillo, Jacob D. Abernethy
An Active Learning Framework using Sparse-Graph Codes for Sparse Polynomials and Graph Sketching
Xiao Li, Kannan Ramchandran
Analysis of Robust PCA via Local Incoherence
Huishuai Zhang, Yi Zhou, Yingbin Liang
A Nonconvex Optimization Framework for Low Rank Matrix Estimation
Tuo Zhao, Zhaoran Wang, Han Liu
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks
Cengiz Pehlevan, Dmitri Chklovskii
Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks
Kevin Scaman, Rémi Lemonnier, Nicolas Vayatis
Approximating Sparse PCA from Incomplete Data
ABHISEK KUNDU, Petros Drineas, Malik Magdon-Ismail
A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA
James R Voss, Mikhail Belkin, Luis Rademacher
A Recurrent Latent Variable Model for Sequential Data
Junyoung Chung, Kyle Kastner, Laurent Dinh et al.
A Reduced-Dimension fMRI Shared Response Model
Po-Hsuan (Cameron) Chen, Janice Chen, Yaara Yeshurun et al.
Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question
Haoyuan Gao, Junhua Mao, Jie Zhou et al.
Associative Memory via a Sparse Recovery Model
Arya Mazumdar, Ankit Singh Rawat
A Structural Smoothing Framework For Robust Graph Comparison
Pinar Yanardag, S.V.N. Vishwanathan
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization
Xiangru Lian, Yijun Huang, Yuncheng Li et al.
Asynchronous stochastic convex optimization: the noise is in the noise and SGD don't care
Sorathan Chaturapruek, John C. Duchi, Christopher Ré
A Theory of Decision Making Under Dynamic Context
Michael Shvartsman, Vaibhav Srivastava, Jonathan D. Cohen
A Tractable Approximation to Optimal Point Process Filtering: Application to Neural Encoding
Yuval Harel, Ron Meir, Manfred Opper
Attention-Based Models for Speech Recognition
Jan K Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk et al.
Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze–like Environments
Dane S Corneil, Wulfram Gerstner
A Universal Catalyst for First-Order Optimization
Hongzhou Lin, Julien Mairal, Zaid Harchaoui
A Universal Primal-Dual Convex Optimization Framework
Alp Yurtsever, Quoc Tran Dinh, Volkan Cevher