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Compositional Semantic Parsing on Semi-Structured Tables
Panupong Pasupat, Percy Liang
Two important aspects of semantic parsing for question answering are the breadth of the knowledge source and the depth of logical compositionality. While existing work trades off o…
On-the-Job Learning with Bayesian Decision Theory
Keenon Werling, Arun Chaganty, Percy Liang +1
Our goal is to deploy a high-accuracy system starting with zero training examples. We consider an "on-the-job" setting, where as inputs arrive, we use real-time crowdsourcing to re…
Traversing Knowledge Graphs in Vector Space
Kelvin Guu, John Miller, Percy Liang
Path queries on a knowledge graph can be used to answer compositional questions such as "What languages are spoken by people living in Lisbon?". However, knowledge graphs often hav…
Reified Context Models
Jacob Steinhardt, Percy Liang
A classic tension exists between exact inference in a simple model and approximate inference in a complex model. The latter offers expressivity and thus accuracy, but the former pr…
Tensor Factorization via Matrix Factorization
Volodymyr Kuleshov, Arun Tejasvi Chaganty, Percy Liang
Tensor factorization arises in many machine learning applications, such knowledge base modeling and parameter estimation in latent variable models. However, numerical methods for t…
Simultaneous diagonalization: the asymmetric, low-rank, and noisy settings
Volodymyr Kuleshov, Arun Tesjavi Chaganty, Percy Liang
Simultaneous matrix diagonalization is used as a subroutine in many machine learning problems, including blind source separation and paramater estimation in latent variable models.…