• Publications
  • Influence
Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
TLDR
We propose a new algorithm MINERVA, which addresses the much more difficult and practical task of answering questions where the relation is known, but only one entity. Expand
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Agent-Human Interactions in the Continuous Double Auction
TLDR
We describe a series of laboratory experiments that, for the first time, allow human subjects to interact with software bidding agents in a CDA. Expand
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Gaussian LDA for Topic Models with Word Embeddings
TLDR
We replace LDA’s parameterization of “topics” as categorical distributions over opaque word types with multivariate Gaussian distributions on the embedding space. Expand
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Utility functions in autonomic systems
TLDR
We present a distributed architecture, implemented in a realistic prototype data center, that demonstrates how utility functions can enable a collection of autonomic elements to continually optimize the use of computational resources in a dynamic, heterogeneous environment. Expand
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Optimal power allocation in server farms
TLDR
We introduce a queueing theoretic model, which allows us to predict the optimal power allocation in a server farm with a fixed power budget, which can significantly improve server farm performance, by a factor of typically 1.4 to 5 in some cases. Expand
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Analyzing Complex Strategic Interactions in Multi-Agent Systems
We develop a model for analyzing complex games with repeated interactions, for which a full game-theoretic analysis is intractable. Our approach treats exogenously specified, heuristic strategies,Expand
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High-performance bidding agents for the continuous double auction
TLDR
We develop two bidding algorithms for real-time Continuous Double Auctions (CDAs) using a variety of market rules that offer what we believe to be the strongest known performance of any published bidding strategy. Expand
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A multi-agent systems approach to autonomic computing
TLDR
Unity is a decentralized architecture for autonomic computing based on multiple interacting agents called autonomic elements. Expand
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Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks
TLDR
We use RNNs to compose the distributed semantics of multi-hop paths in KBs; however for multiple reasons, the approach lacks accuracy and practicality. Expand
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