Papers
Matrix Completion From any Given Set of Observations
Troy Lee, Adi Shraibman
Similarity Component Analysis
Soravit Changpinyo, Kuan Liu, Fei Sha
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces
Mahdi Milani Fard, Yuri Grinberg, Amir-massoud Farahmand et al.
Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic
James L Sharpnack, Akshay Krishnamurthy, Aarti Singh
Analyzing the Harmonic Structure in Graph-Based Learning
Xiao-Ming Wu, Zhenguo Li, Shih-Fu Chang
Distributed Submodular Maximization: Identifying Representative Elements in Massive Data
Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar et al.
Bayesian Mixture Modelling and Inference based Thompson Sampling in Monte-Carlo Tree Search
Aijun Bai, Feng Wu, Xiaoping Chen
The Power of Asymmetry in Binary Hashing
Behnam Neyshabur, Nati Srebro, Ruslan Salakhutdinov et al.
Statistical Active Learning Algorithms
Maria-Florina F Balcan, Vitaly Feldman
Adaptive Anonymity via b-Matching
Krzysztof M Choromanski, Tony Jebara, Kui Tang
Variational Planning for Graph-based MDPs
Qiang Cheng, Qiang Liu, Feng Chen et al.
Correlated random features for fast semi-supervised learning
Brian McWilliams, David Balduzzi, Joachim M Buhmann
Fast Template Evaluation with Vector Quantization
Mohammad Amin Sadeghi, David Forsyth
Fantope Projection and Selection: A near-optimal convex relaxation of sparse PCA
Vincent Q. Vu, Juhee Cho, Jing Lei et al.
q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions
Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions
Tamir Hazan, Subhransu Maji, Joseph Keshet et al.
Estimation Bias in Multi-Armed Bandit Algorithms for Search Advertising
Min Xu, Tao Qin, Tie-Yan Liu
Predicting Parameters in Deep Learning
Misha Denil, Babak Shakibi, Laurent Dinh et al.
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n)
Francis Bach, Eric Moulines
Distributed k-means and k-median Clustering on General Topologies
Maria-Florina F Balcan, Steven Ehrlich, Yingyu Liang
Stochastic Ratio Matching of RBMs for Sparse High-Dimensional Inputs
Yann Dauphin, Yoshua Bengio
Learning Stochastic Inverses
Andreas Stuhlmüller, Jacob Taylor, Noah Goodman
Data-driven Distributionally Robust Polynomial Optimization
Martin Mevissen, Emanuele Ragnoli, Jia Yuan Yu
A memory frontier for complex synapses
Subhaneil Lahiri, Surya Ganguli