Papers
Target Curricula via Selection of Minimum Feature Sets: a Case Study in Boolean Networks
Shannon Fenn, Pablo Moscato
Document Neural Autoregressive Distribution Estimation
Stanislas Lauly, Yin Zheng, Alexandre Allauzen et al.
Efficient Sampling from Time-Varying Log-Concave Distributions
Hariharan Narayanan, Alexer Rakhlin
Approximation Vector Machines for Large-scale Online Learning
Trung Le, Tu Dinh Nguyen, Vu Nguyen et al.
Clustering with Hidden Markov Model on Variable Blocks
Lin Lin, Jia Li
Hinge-Loss Markov Random Fields and Probabilistic Soft Logic
Stephen H. Bach, Matthias Broecheler, Bert Huang et al.
Computational Limits of A Distributed Algorithm for Smoothing Spline
Zuofeng Shang, Guang Cheng
Optimal Dictionary for Least Squares Representation
Mohammed Rayyan Sheriff, Debasish Chatterjee
Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server
Leonard Hasenclever, Stefan Webb, Thibaut Lienart et al.
Accelerating Stochastic Composition Optimization
Mengdi Wang, Ji Liu, Ethan X. Fang
A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation
Thang D. Bui, Josiah Yan, Richard E. Turner
Online Learning to Rank with Top-k Feedback
Sougata Chaudhuri, Ambuj Tewari
Confidence Sets with Expected Sizes for Multiclass Classification
Christophe Denis, Mohamed Hebiri
Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression
Aymeric Dieuleveut, Nicolas Flammarion, Francis Bach
Stability of Controllers for Gaussian Process Dynamics
Julia Vinogradska, Bastian Bischoff, Duy Nguyen-Tuong et al.
Bayesian Network Learning via Topological Order
Young Woong Park, Diego Klabjan
Rank Determination for Low-Rank Data Completion
Morteza Ashraphijuo, Xiaodong Wang, Vaneet Aggarwal
Optimal Rates for Multi-pass Stochastic Gradient Methods
Junhong Lin, Lorenzo Rosasco
openXBOW -- Introducing the Passau Open-Source Crossmodal Bag-of-Words Toolkit
Maximilian Schmitt, Björn Schuller
Fisher Consistency for Prior Probability Shift
Dirk Tasche
An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels
Weiwei Liu, Ivor W. Tsang, Klaus-Robert Müller
Identifying Unreliable and Adversarial Workers in Crowdsourced Labeling Tasks
Srikanth Jagabathula, Lakshminarayanan Subramanian, Ashwin Venkataraman
Distributed Learning with Regularized Least Squares
Shao-Bo Lin, Xin Guo, Ding-Xuan Zhou
A distributed block coordinate descent method for training l1 regularized linear classifiers
Dhruv Mahajan, S. Sathiya Keerthi, S. Sundararajan
A survey of Algorithms and Analysis for Adaptive Online Learning
H. Brendan McMahan