Papers
Labeled Graph Clustering via Projected Gradient Descent
Shiau Hong Lim, Gregory Calvez
Large Scale Empirical Risk Minimization via Truncated Adaptive Newton Method
Mark Eisen, Aryan Mokhtari, Alejandro Ribeiro
Layerwise Systematic Scan: Deep Boltzmann Machines and Beyond
Heng Guo, Kaan Kara, Ce Zhang
Learning Determinantal Point Processes in Sublinear Time
Christophe Dupuy, Francis Bach
Learning Generative Models with Sinkhorn Divergences
Aude Genevay, Gabriel Peyre, Marco Cuturi
Learning Hidden Quantum Markov Models
Siddarth Srinivasan, Geoff Gordon, Byron Boots
Learning linear structural equation models in polynomial time and sample complexity
Asish Ghoshal, Jean Honorio
Learning Priors for Invariance
Eric Nalisnick, Padhraic Smyth
Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity
Asish Ghoshal, Jean Honorio
Learning Structural Weight Uncertainty for Sequential Decision-Making
Ruiyi Zhang, Chunyuan Li, Changyou Chen et al.
Learning to Round for Discrete Labeling Problems
Pritish Mohapatra, Jawahar C.V., M Pawan Kumar
Learning with Complex Loss Functions and Constraints
Harikrishna Narasimhan
Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go?
Chandrashekar Lakshminarayanan, Csaba Szepesvari
Making Tree Ensembles Interpretable: A Bayesian Model Selection Approach
Satoshi Hara, Kohei Hayashi
Matrix completability analysis via graph k-connectivity
Dehua Cheng, Natali Ruchansky, Yan Liu
Matrix-normal models for fMRI analysis
Michael Shvartsman, Narayanan Sundaram, Mikio Aoi et al.
Medoids in Almost-Linear Time via Multi-Armed Bandits
Vivek Bagaria, Govinda Kamath, Vasilis Ntranos et al.
Metrics for Deep Generative Models
Nutan Chen, Alexej Klushyn, Richard Kurle et al.
Minimax-Optimal Privacy-Preserving Sparse PCA in Distributed Systems
Jason Ge, Zhaoran Wang, Mengdi Wang et al.
Minimax Reconstruction Risk of Convolutional Sparse Dictionary Learning
Shashank Singh, Barnabas Poczos, Jian Ma
Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models
Ardavan Saeedi, Matthew Hoffman, Stephen DiVerdi et al.
Multi-objective Contextual Bandit Problem with Similarity Information
Eralp Turgay, Doruk Oner, Cem Tekin
Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations
Alan Lazarus, Dirk Husmeier, Theodore Papamarkou
Multi-scale Nystrom Method
Woosang Lim, Rundong Du, Bo Dai et al.