Papers
Taming the Wild: A Unified Analysis of Hogwild-Style Algorithms
Christopher M De Sa, Ce Zhang, Kunle Olukotun et al.
Copeland Dueling Bandits
Masrour Zoghi, Zohar S Karnin, Shimon Whiteson et al.
Color Constancy by Learning to Predict Chromaticity from Luminance
Ayan Chakrabarti
Community Detection via Measure Space Embedding
Mark Kozdoba, Shie Mannor
Improved Iteration Complexity Bounds of Cyclic Block Coordinate Descent for Convex Problems
Ruoyu Sun, Mingyi Hong
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels
Felipe Tobar, Thang D Bui, Richard E Turner
Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's
Vitaly Feldman, Will Perkins, Santosh Vempala
Deep Temporal Sigmoid Belief Networks for Sequence Modeling
Zhe Gan, Chunyuan Li, Ricardo Henao et al.
Learning From Small Samples: An Analysis of Simple Decision Heuristics
Ozgur Simsek, Marcus Buckmann
Beyond Convexity: Stochastic Quasi-Convex Optimization
Elad Hazan, Kfir Levy, Shai Shalev-Shwartz
Regularized EM Algorithms: A Unified Framework and Statistical Guarantees
Xinyang Yi, Constantine Caramanis
Lifelong Learning with Non-i.i.d. Tasks
Anastasia Pentina, Christoph H. Lampert
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions
Dominik Rothenhäusler, Christina Heinze, Jonas Peters et al.
Fast Distributed k-Center Clustering with Outliers on Massive Data
Gustavo Malkomes, Matt J Kusner, Wenlin Chen et al.
End-To-End Memory Networks
Sainbayar Sukhbaatar, arthur szlam, Jason Weston et al.
Learning visual biases from human imagination
Carl Vondrick, Hamed Pirsiavash, Aude Oliva et al.
Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices
Martin Slawski, Ping Li, Matthias Hein
Approximating Sparse PCA from Incomplete Data
ABHISEK KUNDU, Petros Drineas, Malik Magdon-Ismail
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families
Heiko Strathmann, Dino Sejdinovic, Samuel Livingstone et al.
Online Learning with Gaussian Payoffs and Side Observations
Yifan Wu, András György, Csaba Szepesvari
Estimating Mixture Models via Mixtures of Polynomials
Sida Wang, Arun Tejasvi Chaganty, Percy Liang
Learning Structured Output Representation using Deep Conditional Generative Models
Kihyuk Sohn, Honglak Lee, Xinchen Yan
A Pseudo-Euclidean Iteration for Optimal Recovery in Noisy ICA
James R Voss, Mikhail Belkin, Luis Rademacher
NEXT: A System for Real-World Development, Evaluation, and Application of Active Learning
Kevin G. Jamieson, Lalit Jain, Chris Fernandez et al.