Papers
Scalable MCMC for Mixed Membership Stochastic Blockmodels
Wenzhe Li, Sungjin Ahn, Max Welling
On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System
Yi Zhou, Yaoliang Yu, Wei Dai et al.
Variational Tempering
Stephan Mandt, James McInerney, Farhan Abrol et al.
Sequential Inference for Deep Gaussian Process
Yali Wang, Marcus Brubaker, Brahim Chaib-Draa et al.
Approximate Inference Using DC Programming For Collective Graphical Models
Thien Nguyen, Akshat Kumar, Hoong Chuin Lau et al.
Probabilistic Approximate Least-Squares
Simon Bartels, Philipp Hennig
Fast and Scalable Structural SVM with Slack Rescaling
Heejin Choi, Ofer Meshi, Nathan Srebro
Learning Relationships between Data Obtained Independently
Alexandra Carpentier, Teresa Schlueter
Nonparametric Budgeted Stochastic Gradient Descent
Trung Le, Vu Nguyen, Tu Dinh Nguyen et al.
Batch Bayesian Optimization via Local Penalization
Javier Gonzalez, Zhenwen Dai, Philipp Hennig et al.
New Resistance Distances with Global Information on Large Graphs
Canh Hao Nguyen, Hiroshi Mamitsuka
Fast Dictionary Learning with a Smoothed Wasserstein Loss
Antoine Rolet, Marco Cuturi, Gabriel Peyré
Tractable and Scalable Schatten Quasi-Norm Approximations for Rank Minimization
Fanhua Shang, Yuanyuan Liu, James Cheng
NuC-MKL: A Convex Approach to Non Linear Multiple Kernel Learning
Eli Meirom, Pavel Kisilev
Low-Rank and Sparse Structure Pursuit via Alternating Minimization
Quanquan Gu, Zhaoran Wang Wang, Han Liu
Enumerating Equivalence Classes of Bayesian Networks using EC Graphs
Eunice Yuh-Jie Chen, Arthur Choi Choi, Adnan Darwiche
Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings
Zhitang Chen, Pascal Poupart, Yanhui Geng
Universal Models of Multivariate Temporal Point Processes
Asela Gunawardana, Chris Meek
The Nonparametric Kernel Bayes Smoother
Yu Nishiyama, Amir Afsharinejad, Shunsuke Naruse et al.
Graph Connectivity in Noisy Sparse Subspace Clustering
Yining Wang, Yu-Xiang Wang, Aarti Singh
Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models
Calvin McCarter, Seyoung Kim
Large Scale Distributed Semi-Supervised Learning Using Streaming Approximation
Sujith Ravi, Qiming Diao
A PAC RL Algorithm for Episodic POMDPs
Zhaohan Daniel Guo, Shayan Doroudi, Emma Brunskill
Learning Structured Low-Rank Representation via Matrix Factorization
Jie Shen, Ping Li