Papers
Online Tracking by Learning Discriminative Saliency Map with Convolutional Neural Network
Seunghoon Hong, Tackgeun You, Suha Kwak et al.
Ordinal Mixed Membership Models
Seppo Virtanen, Mark Girolami
Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup
Yufei Ding, Yue Zhao, Xipeng Shen et al.
A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data
Trong Nghia Hoang, Quang Minh Hoang, Bryan Kian Hsiang Low
Online Learning of Eigenvectors
Dan Garber, Elad Hazan, Tengyu Ma
Ordered Stick-Breaking Prior for Sequential MCMC Inference of Bayesian Nonparametric Models
Mrinal Das, Trapit Bansal, Chiranjib Bhattacharyya
Faster Rates for the Frank-Wolfe Method over Strongly-Convex Sets
Dan Garber, Elad Hazan
Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning
K. Lakshmanan, Ronald Ortner, Daniil Ryabko
How Can Deep Rectifier Networks Achieve Linear Separability and Preserve Distances?
Senjian An, Farid Boussaid, Mohammed Bennamoun
A Divide and Conquer Framework for Distributed Graph Clustering
Wenzhuo Yang, Huan Xu
Streaming Sparse Principal Component Analysis
Wenzhuo Yang, Huan Xu
A Unified Framework for Outlier-Robust PCA-like Algorithms
Wenzhuo Yang, Huan Xu
Markov Mixed Membership Models
Aonan Zhang, John Paisley
Landmarking Manifolds with Gaussian Processes
Dawen Liang, John Paisley
Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower Bounds
Yuchen Zhang, Martin Wainwright, Michael Jordan
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe, Christian Szegedy
Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains
Katharina Blechschmidt, Joachim Giesen, Soeren Laue
Budget Allocation Problem with Multiple Advertisers: A Game Theoretic View
Takanori Maehara, Akihiro Yabe, Ken-ichi Kawarabayashi
Pushing the Limits of Affine Rank Minimization by Adapting Probabilistic PCA
Bo Xin, David Wipf
The Benefits of Learning with Strongly Convex Approximate Inference
Ben London, Bert Huang, Lise Getoor
A Provable Generalized Tensor Spectral Method for Uniform Hypergraph Partitioning
Debarghya Ghoshdastidar, Ambedkar Dukkipati
Structural Maxent Models
Corinna Cortes, Vitaly Kuznetsov, Mehryar Mohri et al.
Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs
Stephen Bach, Bert Huang, Jordan Boyd-Graber et al.
Spectral MLE: Top-K Rank Aggregation from Pairwise Comparisons
Yuxin Chen, Changho Suh