Papers
Spectral M-estimation with Applications to Hidden Markov Models
Dustin Tran, Minjae Kim, Finale Doshi-Velez
Randomization and The Pernicious Effects of Limited Budgets on Auction Experiments
Guillaume W. Basse, Hossein Azari Soufiani, Diane Lambert
NYTRO: When Subsampling Meets Early Stopping
Raffaello Camoriano, Tomás Angles, Alessandro Rudi et al.
Loss Bounds and Time Complexity for Speed Priors
Daniel Filan, Jan Leike, Marcus Hutter
Cut Pursuit: Fast Algorithms to Learn Piecewise Constant Functions
Loic Landrieu, Guillaume Obozinski
Back to the Future: Radial Basis Function Networks Revisited
Qichao Que, Mikhail Belkin
Streaming Kernel Principal Component Analysis
Mina Ghashami, Daniel J. Perry, Jeff Phillips
Active Learning Algorithms for Graphical Model Selection
Gautamd Dasarathy, Aarti Singh, Maria-Florina Balcan et al.
Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization
Zhao Song, Ricardo Henao, David Carlson et al.
A Fast and Reliable Policy Improvement Algorithm
Yasin Abbasi-Yadkori, Peter L. Bartlett, Stephen J. Wright
Efficient Sampling for k-Determinantal Point Processes
Chengtao Li, Stefanie Jegelka, Suvrit Sra
Parallel Markov Chain Monte Carlo via Spectral Clustering
Guillaume Basse, Aaron Smith, Natesh Pillai
Private Causal Inference
Matt J. Kusner, Yu Sun, Karthik Sridharan et al.
Communication Efficient Distributed Agnostic Boosting
Shang-Tse Chen, Maria-Florina Balcan, Duen Horng Chau
Towards Stability and Optimality in Stochastic Gradient Descent
Panos Toulis, Dustin Tran, Edo Airoldi
On Lloyd’s Algorithm: New Theoretical Insights for Clustering in Practice
Cheng Tang, Claire Monteleoni
Robust Covariate Shift Regression
Xiangli Chen, Mathew Monfort, Anqi Liu et al.
Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation
Ian En-Hsu Yen, Dmitry Malioutov, Abhishek Kumar
Graph Sparsification Approaches for Laplacian Smoothing
Veeru Sadhanala, Yu-Xiang Wang, Ryan Tibshirani
A Column Generation Bound Minimization Approach with PAC-Bayesian Generalization Guarantees
Jean-Francis Roy, Mario Marchand, François Laviolette
Controlling Bias in Adaptive Data Analysis Using Information Theory
Daniel Russo, James Zou
Provable Tensor Methods for Learning Mixtures of Generalized Linear Models
Hanie Sedghi, Majid Janzamin, Anima Anandkumar
On Searching for Generalized Instrumental Variables
Benito Zander, Maciej Liśkiewicz
Efficient Bregman Projections onto the Permutahedron and Related Polytopes
Cong Han Lim, Stephen J. Wright
Black-Box Policy Search with Probabilistic Programs
Jan-Willem Vandemeent, Brooks Paige, David Tolpin et al.