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Publication search results
found 86 matches
- 2016
- Kareem Amin, Michael P. Wellman, Satinder Singh:
Gradient Methods for Stackelberg Games. UAI 2016 - David T. Arbour, Katerina Marazopoulou, David D. Jensen:
Inferring Causal Direction from Relational Data. UAI 2016 - Mohammad Gheshlaghi Azar, Eva L. Dyer, Konrad P. Körding:
Convex Relaxation Regression: Black-Box Optimization of Smooth Functions by Learning Their Convex Envelopes. UAI 2016 - Matej Balog, Balaji Lakshminarayanan, Zoubin Ghahramani, Daniel M. Roy, Yee Whye Teh:
The Mondrian Kernel. UAI 2016 - Akshay Balsubramani, Aaditya Ramdas:
Sequential Nonparametric Testing with the Law of the Iterated Logarithm. UAI 2016 - Craig Boutilier, Tyler Lu:
Budget Allocation using Weakly Coupled, Constrained Markov Decision Processes. UAI 2016 - Daniele Calandriello, Alessandro Lazaric, Michal Valko:
Analysis of Nyström method with sequential ridge leverage scores. UAI 2016 - Krzysztof Chalupka, Tobias Bischoff, Frederick Eberhardt, Pietro Perona:
Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data. UAI 2016 - Muthukumaran Chandrasekaran, Adam Eck, Prashant Doshi, Leenkiat Soh:
Individual Planning in Open and Typed Agent Systems. UAI 2016 - Morteza Haghir Chehreghani, Mostafa Haghir Chehreghani:
Modeling Transitivity in Complex Networks. UAI 2016 - Junxiang Chen, Jennifer G. Dy:
A Generative Block-Diagonal Model for Clustering. UAI 2016 - Jinghui Chen, Quanquan Gu:
Accelerated Stochastic Block Coordinate Gradient Descent for Sparsity Constrained Nonconvex Optimization. UAI 2016 - Xiangli Chen, Mathew Monfort, Brian D. Ziebart, Peter Carr:
Adversarial Inverse Optimal Control for General Imitation Learning Losses and Embodiment Transfer. UAI 2016 - Jianhui Chen, Tianbao Yang, Qihang Lin, Lijun Zhang, Yi Chang:
Optimal Stochastic Strongly Convex Optimization with a Logarithmic Number of Projections. UAI 2016 - Changying Du, Changde Du, Guoping Long, Qing He, Yucheng Li:
Online Bayesian Multiple Kernel Bipartite Ranking. UAI 2016 - Ralf Eggeling, Mikko Koivisto:
Pruning Rules for Learning Parsimonious Context Trees. UAI 2016 - Jalal Etesami, Negar Kiyavash, Kun Zhang, Kushagra Singhal:
Learning Network of Multivariate Hawkes Processes: A Time Series Approach. UAI 2016 - Francois Fagan, Jalaj Bhandari, John P. Cunningham:
Elliptical Slice Sampling with Expectation Propagation. UAI 2016 - Seth R. Flaxman, Dino Sejdinovic, John P. Cunningham, Sarah Filippi:
Bayesian Learning of Kernel Embeddings. UAI 2016 - James R. Foulds, Joseph Geumlek, Max Welling, Kamalika Chaudhuri:
On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis. UAI 2016 - Roy Fox, Ari Pakman, Naftali Tishby:
Taming the Noise in Reinforcement Learning via Soft Updates. UAI 2016 - Tianfan Fu, Luo Luo, Zhihua Zhang:
Quasi-Newton Hamiltonian Monte Carlo. UAI 2016 - Joseph Futoma, Mark P. Sendak, Blake Cameron, Katherine A. Heller:
Scalable Joint Modeling of Longitudinal and Point Process Data for Disease Trajectory Prediction and Improving Management of Chronic Kidney Disease. UAI 2016 - Tianxiang Gao, Vladimir Jojic:
Degrees of Freedom in Deep Neural Networks. UAI 2016 - Alex Gaunt, Diana Borsa, Yoram Bachrach:
Training Neural Nets to Aggregate Crowdsourced Responses. UAI 2016 - Hugo Gilbert, Bruno Zanuttini, Paul Weng, Paolo Viappiani, Esther Nicart:
Model-Free Reinforcement Learning with Skew-Symmetric Bilinear Utilities. UAI 2016 - Raghuraman Gopalan:
Bridging Heterogeneous Domains With Parallel Transport For Vision and Multimedia Applications. UAI 2016 - Jean Honorio, Tommi S. Jaakkola:
Structured Prediction: From Gaussian Perturbations to Linear-Time Principled Algorithms. UAI 2016 - Hanzhang Hu, Alexander Grubb, J. Andrew Bagnell, Martial Hebert:
Efficient Feature Group Sequencing for Anytime Linear Prediction. UAI 2016 - Viet Huynh, Dinh Q. Phung, Svetha Venkatesh, XuanLong Nguyen, Matthew D. Hoffman, Hung Hai Bui:
Scalable Nonparametric Bayesian Multilevel Clustering. UAI 2016
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