Papers
LAMORE: A Stable, Scalable Approach to Latent Vector Autoregressive Modeling of Categorical Time Series
Yubin Park, Carlos Carvalho, Joydeep Ghosh
Latent Gaussian Models for Topic Modeling
Changwei Hu, Eunsu Ryu, David Carlson et al.
Learning and Evaluation in Presence of Non-i.i.d. Label Noise
Nico Görnitz, Anne Porbadnigk, Alexander Binder et al.
Learning Bounded Tree-width Bayesian Networks using Integer Linear Programming
Pekka Parviainen, Hossein Shahrabi Farahani, Jens Lagergren
Learning Heterogeneous Hidden Markov Random Fields
Jie Liu, Chunming Zhang, Elizabeth Burnside et al.
Learning Optimal Bounded Treewidth Bayesian Networks via Maximum Satisfiability
Jeremias Berg, Matti Järvisalo, Brandon Malone
Learning Structured Models with the AUC Loss and Its Generalizations
Nir Rosenfeld, Ofer Meshi, Danny Tarlow et al.
Learning with Maximum A-Posteriori Perturbation Models
Andreea Gane, Tamir Hazan, Tommi Jaakkola
Lifted MAP Inference for Markov Logic Networks
Somdeb Sarkhel, Deepak Venugopal, Parag Singla et al.
Linear-time training of nonlinear low-dimensional embeddings
Max Vladymyrov, Miguel Carreira-Perpinan
Loopy Belief Propagation in the Presence of Determinism
David Smith, Vibhav Gogate
Low-Rank Spectral Learning
Alex Kulesza, N. Raj Rao, Satinder Singh
Mixed Graphical Models via Exponential Families
Eunho Yang, Yulia Baker, Pradeep Ravikumar et al.
Near Optimal Bayesian Active Learning for Decision Making
Shervin Javdani, Yuxin Chen, Amin Karbasi et al.
Non-Asymptotic Analysis of Relational Learning with One Network
Peng He, Changshui Zhang
Nonparametric estimation and testing of exchangeable graph models
Justin Yang, Christina Han, Edoardo Airoldi
On correlation and budget constraints in model-based bandit optimization with application to automatic machine learning
Matthew Hoffman, Bobak Shahriari, Nando Freitas
On Estimating Causal Effects based on Supplemental Variables
Takahiro Hayashi, Manabu Kuroki
Online Passive-Aggressive Algorithms for Non-Negative Matrix Factorization and Completion
Mathieu Blondel, Yotaro Kubo, Ueda Naonori
On the Testability of Models with Missing Data
Karthika Mohan, Judea Pearl
Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors
Junya Honda, Akimichi Takemura
PAC-Bayesian Collective Stability
Ben London, Bert Huang, Ben Taskar et al.
PAC-Bayesian Theory for Transductive Learning
Luc Bégin, Pascal Germain, François Laviolette et al.
Pan-sharpening with a Bayesian nonparametric dictionary learning model
Xinghao Ding, Yiyong Jiang, Yue Huang et al.