Papers
Logistic Regression: Tight Bounds for Stochastic and Online Optimization
Elad Hazan, Tomer Koren, Kfir Y. Levy
A second-order bound with excess losses
Pierre Gaillard, Gilles Stoltz, Tim van Erven
Community Detection via Random and Adaptive Sampling
Se-Young Yun, Alexandre Proutiere
Learning Sparsely Used Overcomplete Dictionaries
Alekh Agarwal, Animashree Anandkumar, Prateek Jain et al.
Multiarmed Bandits With Limited Expert Advice
Satyen Kale
Bayes-Optimal Scorers for Bipartite Ranking
Aditya Krishna Menon, Robert C. Williamson
Uniqueness of Ordinal Embedding
Matthäus Kleindessner, Ulrike Luxburg
Learning without concentration
Shahar Mendelson
Distribution-independent Reliable Learning
Varun Kanade, Justin Thaler
Open Problem: Efficient Online Sparse Regression
Satyen Kale
Open Problem: Shifting Experts on Easy Data
Manfred K. Warmuth, Wouter M. Koolen
Open Problem: Online Local Learning
Paul Christiano
Open Problem: Finding Good Cascade Sampling Processes for the Network Inference Problem
Manuel Gomez-Rodriguez, Le Song, Bernhard Schoelkopf
Open Problem: Tightness of maximum likelihood semidefinite relaxations
Afonso S. Bandeira, Yuehaw Khoo, Amit Singer
Heterogeneous Domain Adaptation for Multiple Classes
Joey Tianyi Zhou, Ivor W.Tsang, Sinno Jialin Pan et al.
Accelerated Stochastic Gradient Method for Composite Regularization
Wenliang Zhong, James Kwok
Efficient Transfer Learning Method for Automatic Hyperparameter Tuning
Dani Yogatama, Gideon Mann
Generating Efficient MCMC Kernels from Probabilistic Programs
Lingfeng Yang, Patrick Hanrahan, Noah Goodman
Nonparametric estimation and testing of exchangeable graph models
Justin Yang, Christina Han, Edoardo Airoldi
Context Aware Group Nearest Shrunken Centroids in Large-Scale Genomic Studies
Juemin Yang, Fang Han, Rafael Irizarry et al.
Mixed Graphical Models via Exponential Families
Eunho Yang, Yulia Baker, Pradeep Ravikumar et al.
Dynamic Resource Allocation for Optimizing Population Diffusion
Shan Xue, Alan Fern, Daniel Sheldon