Papers
Connected Sub-graph Detection
Jing Qian, Venkatesh Saligrama, Yuting Chen
An inclusion optimal algorithm for chain graph structure learning
Jose Peña, Dag Sonntag, Jens Nielsen
Expectation Propagation for Likelihoods Depending on an Inner Product of Two Multivariate Random Variables
Tomi Peltola, Pasi Jylänki, Aki Vehtari
An Efficient Algorithm for Large Scale Compressive Feature Learning
Hristo Paskov, John Mitchell, Trevor Hastie
Learning Bounded Tree-width Bayesian Networks using Integer Linear Programming
Pekka Parviainen, Hossein Shahrabi Farahani, Jens Lagergren
Spoofing Large Probability Mass Functions to Improve Sampling Times and Reduce Memory Costs
Jon Parker, Hans Engler
LAMORE: A Stable, Scalable Approach to Latent Vector Autoregressive Modeling of Categorical Time Series
Yubin Park, Carlos Carvalho, Joydeep Ghosh
To go deep or wide in learning?
Gaurav Pandey, Ambedkar Dukkipati
FuSSO: Functional Shrinkage and Selection Operator
Junier Oliva, Barnabas Poczos, Timothy Verstynen et al.
Fast Distribution To Real Regression
Junier Oliva, Willie Neiswanger, Barnabas Poczos et al.
Scaling Nonparametric Bayesian Inference via Subsample-Annealing
Fritz Obermeyer, Jonathan Glidden, Eric Jonas
Joint Structure Learning of Multiple Non-Exchangeable Networks
Chris Oates, Sach Mukherjee
Robust Forward Algorithms via PAC-Bayes and Laplace Distributions
Asaf Noy, Koby Crammer
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence
Yung-Kyun Noh, Masashi Sugiyama, Song Liu et al.
The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling
Willie Neiswanger, Frank Wood, Eric Xing
Selective Sampling with Drift
Edward Moroshko, Koby Crammer
On the Testability of Models with Missing Data
Karthika Mohan, Judea Pearl
A Geometric Algorithm for Scalable Multiple Kernel Learning
John Moeller, Parasaran Raman, Suresh Venkatasubramanian et al.
Efficient Lifting of MAP LP Relaxations Using k-Locality
Martin Mladenov, Kristian Kersting, Amir Globerson
Interpretable Sparse High-Order Boltzmann Machines
Martin Renqiang Min, Xia Ning, Chao Cheng et al.
Active Boundary Annotation using Random MAP Perturbations
Subhransu Maji, Tamir Hazan, Tommi Jaakkola
Active Area Search via Bayesian Quadrature
Yifei Ma, Roman Garnett, Jeff Schneider
PAC-Bayesian Collective Stability
Ben London, Bert Huang, Ben Taskar et al.
Learning Heterogeneous Hidden Markov Random Fields
Jie Liu, Chunming Zhang, Elizabeth Burnside et al.