Artificial Intelligence
Pursuing computing advances to create intelligent machines that complement human reasoning to augment and enrich our experience and competencies.
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NIPS: Oral Session 10 – Lirong Xia
In this paper, we take a statistical decision-theoretic viewpoint on social choice, putting a focus on the decision to be made on behalf of a system of agents. In our framework, we are given a…
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NIPS: Spotlight Session 9 – Graphical Models Spotlights, Model Selection
S. Nie, D. Maua, C. de Campos, Q. Ji Advances in Learning Bayesian Networks of Bounded Treewidth J. Tristan, D. Huang, J. Tassarotti, A. Pocock, S. Green, G. Steele Augur: Data-Parallel Probabilistic Modeling N. Ruozzi,…
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NIPS: Spotlight Session 10 – Cognitive Science Spotlights
M. Irfan, L. Ortiz Causal Strategic Inference in Networked Microfinance Economies D. Eigen, C. Puhrsch, R. Fergus Depth Map Prediction from a Single Image using a Multi-Scale Deep Network J. Drugowitsch, R. Moreno-Bote, A. Pouget…
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NIPS: Oral Session 9 – Cynthia Dwork
Privacy-preserving data analysis has a large literature that spans several disciplines. Many early attempts have proved problematic either in practice or on paper. A new approach, “differential privacy” — a notion tailored to situations in…
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NIPS: Oral Session 10 – Michael Kearns
Beginning with the introduction of graphical games and related models, there is now a rich body of algorithmic connections between probabilistic inference, game theory and microeconomics. Strategic analogues of belief propagation and other inference techniques…
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NIPS: Oral Session 9 – Adrian Weller
It was recently proved using graph covers (Ruozzi, 2012) that the Bethe partition function is upper bounded by the true partition function for a binary pairwise model that is attractive. Here we provide a new,…
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NIPS: Spotlight Session 7: Reinforcement Learning Spotlights
B. Piot, M. Geist, O. Pietquin Difference of Convex Functions Programming for Reinforcement Learning S. Levine, P. Abbeel Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics I. Osband, B. Van Roy Near-optimal…
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NIPS: Oral Session 6 – Wei Chen
Combinatorial Pure Exploration of Multi-Armed Bandits We study the {\em combinatorial pure exploration (CPE)} problem in the stochastic multi-armed bandit setting, where a learner explores a set of arms with the objective of identifying the…
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A Wild Bootstrap for Degenerate Kernel Tests
A wild bootstrap method for nonparametric hypothesis tests based on kernel distribution embeddings is proposed. This bootstrap method is used to construct provably consistent tests that apply to random processes, for which the naive permutation-based…
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NIPS: Spotlight Session 6 – Learning Theory Spotlights
C. Zhang, K. Chaudhuri Beyond Disagreement-Based Agnostic Active Learning A. Sani, G. Neu, A. Lazaric Exploiting easy data in online optimization P. Awasthi, A. Blum, O. Sheffet, A. Vijayaraghavan Learning Mixtures of Ranking Models M.…
