Papers
Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification
Junfeng Wen, Chun-Nam Yu, Russell Greiner
Stochastic Neighbor Compression
Matt Kusner, Stephen Tyree, Kilian Weinberger et al.
Alternating Minimization for Mixed Linear Regression
Xinyang Yi, Constantine Caramanis, Sujay Sanghavi
Fast large-scale optimization by unifying stochastic gradient and quasi-Newton methods
Jascha Sohl-Dickstein, Ben Poole, Surya Ganguli
Multimodal Neural Language Models
Ryan Kiros, Ruslan Salakhutdinov, Rich Zemel
Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting
Oscar Beijbom, Mohammad Saberian, David Kriegman et al.
On Robustness and Regularization of Structural Support Vector Machines
Mohamad Ali Torkamani, Daniel Lowd
A new Q(lambda) with interim forward view and Monte Carlo equivalence
Rich Sutton, Ashique Rupam Mahmood, Doina Precup et al.
Model-Based Relational RL When Object Existence is Partially Observable
Ngo Ahn Vien, Marc Toussaint
Local algorithms for interactive clustering
Pranjal Awasthi, Maria Balcan, Konstantin Voevodski
Least Squares Revisited: Scalable Approaches for Multi-class Prediction
Alekh Agarwal, Sham Kakade, Nikos Karampatziakis et al.
Latent Semantic Representation Learning for Scene Classification
Xin Li, Yuhong Guo
Scaling SVM and Least Absolute Deviations via Exact Data Reduction
Jie Wang, Peter Wonka, Jieping Ye
Memory (and Time) Efficient Sequential Monte Carlo
Seong-Hwan Jun, Alexandre Bouchard-Côté
Linear Time Solver for Primal SVM
Feiping Nie, Yizhen Huang, Heng Huang
Linear Programming for Large-Scale Markov Decision Problems
Alan Malek, Yasin Abbasi-Yadkori, Peter Bartlett
Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm
Alexander Schwing, Tamir Hazan, Marc Pollefeys et al.
Consistency of Causal Inference under the Additive Noise Model
Samory Kpotufe, Eleni Sgouritsa, Dominik Janzing et al.
An Asynchronous Parallel Stochastic Coordinate Descent Algorithm
Ji Liu, Steve Wright, Christopher Re et al.
Optimization Equivalence of Divergences Improves Neighbor Embedding
Zhirong Yang, Jaakko Peltonen, Samuel Kaski
An Analysis of State-Relevance Weights and Sampling Distributions on L1-Regularized Approximate Linear Programming Approximation Accuracy
Gavin Taylor, Connor Geer, David Piekut
Structured Prediction of Network Response
Hongyu Su, Aristides Gionis, Juho Rousu
Gaussian Process Classification and Active Learning with Multiple Annotators
Filipe Rodrigues, Francisco Pereira, Bernardete Ribeiro
Sparse Reinforcement Learning via Convex Optimization
Zhiwei Qin, Weichang Li, Firdaus Janoos
Bayesian Max-margin Multi-Task Learning with Data Augmentation
Chengtao Li, Jun Zhu, Jianfei Chen