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A Bayesian Matrix Factorization Model for Relational Data |
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Ajit Singh
, Geoffrey Gordon
|
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A Convex Formulation for Learning Task Relationships in Multi-Task Learning |
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Yu Zhang
, Dit-Yan Yeung
|
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A Delayed Column Generation Strategy for Exact k-Bounded MAP Inference in Markov Logic Networks |
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Mathias Niepert
|
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A Family of Computationally Efficient and Simple Estimators for Unnormalized Statistical Models |
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Miika Pihlaja
, Michael Gutmann
, Aapo Hyvarinen
|
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A Scalable Method for Solving High-Dimensional Continuous POMDPs Using Local Approximation |
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Tom Erez
, William Smart
|
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ALARMS: Alerting and Reasoning Management System for Next Generation Aircraft Hazards |
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Alan Carlin
, Nathan Schurr
, Janusz Marecki
|
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Algorithms and Complexity Results for Exact Bayesian Structure Learning |
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Sebastian Ordyniak
, Stefan Szeider
|
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An Online Learning-based Framework for Tracking |
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Kamalika Chaudhuri
, Yoav Freund
, Daniel Hsu
|
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Anytime Planning for Decentralized POMDPs using Expectation Maximization |
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Akshat Kumar
, Shlomo Zilberstein
|
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Approximating Higher-Order Distances Using Random Projections |
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Ping Li
, Michael Mahoney
, Yiyuan She
|
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Automated Planning in Repeated Adversarial Games |
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Enrique Munoz de Cote
, Archie Chapman
, Adam Sykulski
, Nicholas Jennings
|
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Automatic Tuning of Interactive Perception Applications |
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Qian Zhu
, Branislav Kveton
, Lily Mummert
, Padmanabhan Pillai
|
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Bayesian exponential family projections for coupled data sources |
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Arto Klami
, Seppo Virtanen
, Samuel Kaski
|
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Bayesian Inference in Monte-Carlo Tree Search |
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Gerald Tesauro
, V Rajan
, Richard Segal
|
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Bayesian Model Averaging Using the k-best Bayesian Network Structures |
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Jin Tian
, Ru He
, Lavanya Ram
|
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Bayesian Rose Trees |
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Charles Blundell
, Yee Whye Teh
, Katherine Heller
|
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BEEM : Bucket Elimination with External Memory |
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Kalev Kask
, Rina Dechter
, Andrew Gelfand
|
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Causal Conclusions that Flip Repeatedly and Their Justification |
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Kevin Kelly
, Conor Mayo-Wilson
|
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Characterizing the Set of Coherent Lower Previsions with a Finite Number of Constraints or Vertices |
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Erik Quaeghebeur
|
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Combining Spatial and Telemetric Features for Learning Animal Movement Models |
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Berk Kapicioglu
, Robert Schapire
, Martin Wikelski
, Tamara Broderick
|
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Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker |
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Farheen Omar
, Mathieu Sinn
, Jakub Truszkowski
, Pascal Poupart
, James Tung
, Allen Caine
|
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Compiling Possibilistic Networks: Alternative Approaches to Possibilistic Inference |
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Raouia Ayachi
, Nahla Ben Amor
, Salem Benferhat
, Rolf Haenni
|
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Confounding Equivalence in Causal Inference |
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Judea Pearl
, Azaria Paz
|
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Convergent and Correct Message Passing Schemes for Optimization Problems over Graphical Models |
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Nicholas Ruozzi
, Sekhar Tatikonda
|
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Dirichlet Process Mixtures of Generalized Mallows Models |
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Marina Meila
, Harr Chen
|
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Distribution over Beliefs for Memory Bounded Dec-POMDP Planning |
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Gabriel Corona
, Francois Charpillet
|
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Dynamic programming in in uence diagrams with decision circuits |
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Ross Shachter
, Debarun Bhattacharjya
|
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Efficient Clustering with Limited Distance Information |
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Konstantin Voevodski
, Maria-Florina Balcan
, Heiko Roglin
, Shang-Hua Teng
, Yu Xia
|
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Exact and Approximate Inference in Associative Hierarchical Networks using Graph Cuts |
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Chris Russell
, L'ubor Ladicky
, Pushmeet Kohli
, Philip Torr
|
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Formula-Based Probabilistic Inference |
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Vibhav Gogate
, Pedro Domingos
|
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Gaussian Process Structural Equation Models with Latent Variables |
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Ricardo Silva
, Robert Gramacy
|
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Gaussian Process Topic Models |
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Amrudin Agovic
, Arindam Banerjee
|
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Gibbs Sampling in Open-Universe Stochastic Languages |
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Nimar Arora
, Rodrigo de Salvo Braz
, Erik Sudderth
, Stuart Russell
|
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GraphLab: A New Framework For Parallel Machine Learning |
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Yucheng Low
, Joseph Gonzalez
, Aapo Kyrola
, Danny Bickson
, Carlos Guestrin
, Joseph Hellerstein
|
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Hybrid Generative/Discriminative Learning for Automatic Image Annotation |
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Shuang Yang
, Jiang Bian
, Hongyuan Zha
|
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Identifying Causal Effects with Computer Algebra |
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Luis Garcia
, Sarah Spielvogel
, Seth Sullivant
|
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Incorporating Side Information in Probabilistic Matrix Factorization with Gaussian Processes |
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Ryan Adams
, George Dahl
, Iain Murray
|
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Inference by Minimizing Size, Divergence, or their Sum |
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Sebastian Riedel
, David Smith
, Andrew McCallum
|
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Inference-less Density Estimation using Copula Bayesian Networks |
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Gal Elidan
|
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Inferring deterministic causal relations |
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Povilas Daniusis
, Dominik Janzing
, Joris Mooij
, Jakob Zscheischler
, Bastian Steudel
, Kun Zhang
, Bernhard Schoelkopf
|
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Intracluster Moves for Constrained Discrete-Space MCMC |
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Firas Hamze
, Nando de Freitas
|
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Invariant Gaussian Process Latent Variable Models and Application in Causal Discovery |
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Kun Zhang
, Bernhard Schoelkopf
, Dominik Janzing
|
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Irregular-Time Bayesian Networks |
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Michael Ramati
, Yuval Shahar
|
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Learning Game Representations from Data Using Rationality Constraints |
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Xi Gao
, Avi Pfeffer
|
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Learning networks determined by the ratio of prior and data |
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Maomi Ueno
|
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Learning Structural Changes of Gaussian Graphical Models in Controlled Experiments |
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Bai Zhang
, Yue Wang
|
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Learning Why Things Change: The Difference-Based Causality Learner |
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Mark Voortman
, Denver Dash
, Marek Druzdzel
|
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Lifted Inference for Relational Continuous Models |
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Jaesik Choi
, Eyal Amir
, David Hill
|
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Matrix Coherence and the Nystrom Method |
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Ameet Talwalkar
, Afshin Rostamizadeh
|
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Maximizing the Spread of Cascades Using Network Design |
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Daniel Sheldon
, Bistra Dilkina
, Adam Elmachtoub
, Ryan Finseth
, Ashish Sabharwal
, Jon Conrad
, Carla Gomes
, David Shmoys
, William Allen
, Ole Amundsen
, William Vaughan
|
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Maximum likelihood fitting of acyclic directed mixed graphs to binary data |
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Robin Evans
, Thomas Richardson
|
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MDPs with Unawareness |
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Joseph Halpern
, Nan Rong
, Ashutosh Saxena
|
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Merging Knowledge Bases in Possibilistic Logic by Lexicographic Aggregation |
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Guilin Qi
, Jianfeng Du
, Weiru Liu
, David Bell
|
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Modeling Events with Cascades of Poisson Processes |
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Aleksandr Simma
, Michael Jordan
|
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Modeling Multiple Annotator Expertise in the Semi-Supervised Learning Scenario |
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Yan Yan
, Romer Rosales
, Glenn Fung
, Jennifer Dy
|
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Multi-Domain Collaborative Filtering |
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Yu Zhang
, Bin Cao
, Dit-Yan Yeung
|
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Negative Tree Reweighted Belief Propagation |
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Qiang Liu
, Alexander Ihler
|
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On a Class of Bias-Amplifying Variables that Endanger Effect Estimates |
|
Judea Pearl
|
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On Measurement Bias in Causal Inference |
|
Judea Pearl
|
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On the Validity of Covariate Adjustment for Estimating Causal Effects |
|
Ilya Shpitser
, Tyler VanderWeele
, James Robins
|
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Online Semi-Supervised Learning on Quantized Graphs |
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Michal Valko
, Branislav Kveton
, Ling Huang
, Daniel Ting
|
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Parameter-Free Spectral Kernel Learning |
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Qi Mao
, Ivor Tsang
|
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Parametric Return Density Estimation for Reinforcement Learning |
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Tetsuro Morimura
, Masashi Sugiyama
, Hisashi Kashima
, Hirotaka Hachiya
, Toshiyuki Tanaka
|
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Playing games against nature: optimal policies for renewable resource allocation |
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Stefano Ermon
, Jon Conrad
, Carla Gomes
, Bart Selman
|
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Possibilistic Answer Set Programming Revisited |
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Kim Bauters
, Steven Schockaert
, Martine De Cock
, Dirk Vermeir
|
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Prediction with Advice of Unknown Number of Experts |
|
Alexey Chernov
, Vladimir Vovk
|
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Primal View on Belief Propagation |
|
Tomas Werner
|
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Probabilistic Similarity Logic |
|
Matthias Brocheler
, Lilyana Mihalkova
, Lise Getoor
|
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RAPID: A Reachable Anytime Planner for Imprecisely-sensed Domains |
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Emma Brunskill
, Stuart Russell
|
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Real-Time Scheduling via Reinforcement Learning |
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Robert Glaubius
, Terry Tidwell
, Christopher Gill
, William Smart
|
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Regularized Maximum Likelihood for Intrinsic Dimension Estimation |
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Mithun Das Gupta
, Thomas Huang
|
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Risk Sensitive Path Integral Control |
|
Bart van den Broek
, Wim Wiegerinck
, Hilbert Kappen
|
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Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost |
|
Ping Li
|
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Robust Metric Learning by Smooth Optimization |
|
Kaizhu Huang
, Rong Jin
, Zenglin Xu
, Cheng-Lin Liu
|
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Rollout Sampling Policy Iteration for Decentralized POMDPs |
|
Feng Wu
, Shlomo Zilberstein
, Xiaoping Chen
|
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Solving Hybrid Influence Diagrams with Deterministic Variables |
|
Yijing Li
, Prakash Shenoy
|
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Solving Multistage Influence Diagrams using Branch-and-Bound Search |
|
Changhe Yuan
, Xiaojian Wu
, Eric Hansen
|
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Source Separation and Higher-Order Causal Analysis of MEG and EEG |
|
Kun Zhang
, Aapo Hyvarinen
|
|
Sparse-posterior Gaussian Processes for general likelihoods |
|
Yuan (Alan) Qi
, Ahmed Abdel-Gawad
, Thomas Minka
|
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Speeding up the binary Gaussian process classification |
|
Jarno Vanhatalo
, Aki Vehtari
|
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Super-Samples from Kernel Herding |
|
Yutian Chen
, Max Welling
, Alex Smola
|
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The Cost of Troubleshooting Cost Clusters with Inside Information |
|
Thorsten Ottosen
, Finn Jensen
|
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The Hierarchical Dirichlet Process Hidden Semi-Markov Model |
|
Matthew Johnson
, Alan Willsky
|
|
Three new sensitivity analysis methods for influence diagrams |
|
Debarun Bhattacharjya
, Ross Shachter
|
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Timeline: A Dynamic Hierarchical Dirichlet Process Model for Recovering Birth/Death and Evolution of Topics in Text Stream |
|
Amr Ahmed
, Eric Xing
|
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Truthful Feedback for Sanctioning Reputation Mechanisms |
|
Jens Witkowski
|
|
Understanding Sampling Style Adversarial Search Methods |
|
Raghuram Ramanujan
, Ashish Sabharwal
, Bart Selman
|
|
Variance-Based Rewards for Approximate Bayesian Reinforcement Learning |
|
Jonathan Sorg
, Satinder Singh
, Richard Lewis
|
