Papers
Semi-Crowdsourced Clustering: Generalizing Crowd Labeling by Robust Distance Metric Learning
Jinfeng Yi, Rong Jin, Shaili Jain et al.
Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL
Nishant Mehta, Dongryeol Lee, Alexander G. Gray
Entangled Monte Carlo
Seong-hwan Jun, Liangliang Wang, Alexandre Bouchard-côté
Optimal kernel choice for large-scale two-sample tests
Arthur Gretton, Dino Sejdinovic, Heiko Strathmann et al.
Submodular-Bregman and the Lovász-Bregman Divergences with Applications
Rishabh Iyer, Jeff A. Bilmes
Affine Independent Variational Inference
Edward Challis, David Barber
Bayesian Warped Gaussian Processes
Miguel Lázaro-Gredilla
Learning to Align from Scratch
Gary Huang, Marwan Mattar, Honglak Lee et al.
Learning Networks of Heterogeneous Influence
Nan Du, Le Song, Ming Yuan et al.
Scalable Inference of Overlapping Communities
Prem Gopalan, Sean Gerrish, Michael Freedman et al.
Assessing Blinding in Clinical Trials
Ognjen Arandjelovic
Spectral learning of linear dynamics from generalised-linear observations with application to neural population data
Lars Buesing, Jakob H. Macke, Maneesh Sahani
Semantic Kernel Forests from Multiple Taxonomies
Sung Ju Hwang, Kristen Grauman, Fei Sha
Feature-aware Label Space Dimension Reduction for Multi-label Classification
Yao-nan Chen, Hsuan-tien Lin
Majorization for CRFs and Latent Likelihoods
Tony Jebara, Anna Choromanska
Fiedler Random Fields: A Large-Scale Spectral Approach to Statistical Network Modeling
Antonino Freno, Mikaela Keller, Marc Tommasi
A Polylog Pivot Steps Simplex Algorithm for Classification
Elad Hazan, Zohar Karnin
Communication/Computation Tradeoffs in Consensus-Based Distributed Optimization
Konstantinos Tsianos, Sean Lawlor, Michael G. Rabbat
Robustness and risk-sensitivity in Markov decision processes
Takayuki Osogami
Multiple Choice Learning: Learning to Produce Multiple Structured Outputs
Abner Guzmán-rivera, Dhruv Batra, Pushmeet Kohli
Tractable Objectives for Robust Policy Optimization
Katherine Chen, Michael Bowling
Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding
Philip Sterne, Joerg Bornschein, Abdul-saboor Sheikh et al.
Variational Inference for Crowdsourcing
Qiang Liu, Jian Peng, Alex Ihler
Multiplicative Forests for Continuous-Time Processes
Jeremy Weiss, Sriraam Natarajan, David Page
Generalization Bounds for Domain Adaptation
Chao Zhang, Lei Zhang, Jieping Ye