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AutoRec: Autoencoders Meet Collaborative Filtering
TLDR
This paper proposes AutoRec, a novel autoencoder framework for collaborative filtering (CF). Expand
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A Survey of the Seventh International Planning Competition
TLDR
In this article we review the 2011 International Planning Competition. Expand
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Improving LDA topic models for microblogs via tweet pooling and automatic labeling
TLDR
We investigate methods to improve topics learned from Twitter content without modifying the basic machinery of LDA; we achieve this through various pooling schemes that aggregate tweets in a data preprocessing step. Expand
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The 2014 International Planning Competition: Progress and Trends
TLDR
We review the 2014 International Planning Competition (IPC-2014), the eighth in a series of competitions starting in 1998. Expand
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Algorithms for Direct 0-1 Loss Optimization in Binary Classification
TLDR
We explore a variety of practical methods for direct (approximate) optimization of the 0–1 loss based on branch and bound search, combinatorial search, and coordinate descent on smooth, differentiable relaxations of 0-1 loss. Expand
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Practical solution techniques for first-order MDPs
TLDR
We propose one such approach that translates an expressive subset of the PPDDL representation to a first-order MDP (FOMDP) specification and then derives a domain-independent policy without grounding at any intermediate step. Expand
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Real-time Multiattribute Bayesian Preference Elicitation with Pairwise Comparison Queries
TLDR
We introduce an approximate PE framework based on a variant of TrueSkill for performing efficient closed-form Bayesian updates and query selection for a multiattribute utility belief state — a novel PE approach that naturally facilitates the efficient evaluation of value of information (VOI). Expand
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Expecting to be HIP: Hawkes Intensity Processes for Social Media Popularity
TLDR
We develop a novel mathematical model, the Hawkes intensity process, which can explain the complex popularity history of each video according to its type of content, network of diffusion, and sensitivity to promotion. Expand
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Symbolic Variable Elimination for Discrete and Continuous Graphical Models
TLDR
We introduce SVE - a symbolic extension of the well-known variable elimination algorithm to perform exact inference in an expressive class of mixed discrete and continuous variable graphical models whose conditional probability functions can be well-approximated as oblique piecewise polynomials with bounded support. Expand
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Symbolic Dynamic Programming for First-order POMDPs
TLDR
We show that it is also possible to exploit the full expressive power of first-order quantification to achieve state, action, and observation abstraction in a dynamic programming solution to relationally specified POMDPs. Expand
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