Papers
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
An Improved Convergence Analysis of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
Xingguo Li, Tuo Zhao, Raman Arora et al.
Quantization based Fast Inner Product Search
Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski et al.
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA
Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu
Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree
Chen-Yu Lee, Patrick W. Gallagher, Zhuowen Tu
Geometry Aware Mappings for High Dimensional Sparse Factors
Avradeep Bhowmik, Nathan Liu, Erheng Zhong et al.
Simple and Scalable Constrained Clustering: a Generalized Spectral Method
Mihai Cucuringu, Ioannis Koutis, Sanjay Chawla et al.
PAC-Bayesian Bounds based on the Rényi Divergence
Luc Bégin, Pascal Germain, François Laviolette et al.
Optimal Statistical and Computational Rates for One Bit Matrix Completion
Renkun Ni, Quanquan Gu
A Lasso-based Sparse Knowledge Gradient Policy for Sequential Optimal Learning
Yan Li, Han Liu, Warren Powell
Bayesian Generalised Ensemble Markov Chain Monte Carlo
Jes Frellsen, Ole Winther, Zoubin Ghahramani et al.
K2-ABC: Approximate Bayesian Computation with Kernel Embeddings
Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic
Latent Point Process Allocation
Chris Lloyd, Tom Gunter, Michael Osborne et al.
Nearly Optimal Classification for Semimetrics
Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch
Deep Kernel Learning
Andrew Gordon Wilson, Zhiting Hu, Ruslan Salakhutdinov et al.
Multi-Level Cause-Effect Systems
Krzysztof Chalupka, Frederick Eberhardt, Pietro Perona
Unsupervised Ensemble Learning with Dependent Classifiers
Ariel Jaffe, Ethan Fetaya, Boaz Nadler et al.
Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation
Søren Hauberg, Oren Freifeld, Anders Boesen Lindbo Larsen et al.
Bayesian Markov Blanket Estimation
Dinu Kaufmann, Sonali Parbhoo, Aleksander Wieczorek et al.