Papers
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.
Hidden Technical Debt in Machine Learning Systems
D. Sculley, Gary Holt, Daniel Golovin et al.
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks
Cengiz Pehlevan, Dmitri Chklovskii
Consistent Multilabel Classification
Oluwasanmi O Koyejo, Nagarajan Natarajan, Pradeep K Ravikumar et al.
On the Optimality of Classifier Chain for Multi-label Classification
Weiwei Liu, Ivor Tsang
Linear Multi-Resource Allocation with Semi-Bandit Feedback
Tor Lattimore, Koby Crammer, Csaba Szepesvari
Structured Transforms for Small-Footprint Deep Learning
Vikas Sindhwani, Tara Sainath, Sanjiv Kumar
Efficient Thompson Sampling for Online Matrix-Factorization Recommendation
Jaya Kawale, Hung H Bui, Branislav Kveton et al.
An Active Learning Framework using Sparse-Graph Codes for Sparse Polynomials and Graph Sketching
Xiao Li, Kannan Ramchandran
Principal Differences Analysis: Interpretable Characterization of Differences between Distributions
Jonas W Mueller, Tommi Jaakkola