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Eric P. Xing
Researcher at Carnegie Mellon University
Publications - 725
Citations - 48035
Eric P. Xing is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Inference & Topic model. The author has an hindex of 99, co-authored 711 publications receiving 41467 citations. Previous affiliations of Eric P. Xing include Microsoft & Intel.
Papers
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Proceedings Article
Markov Network Estimation From Multi-attribute Data
TL;DR: This paper proposes a new principled framework for estimating multi-attribute graphs, which estimates the partial canonical correlations that naturally accommodate complex nodal features.
Proceedings Article
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering
TL;DR: This paper proposes a specific and shared causal model (SSCM), which takes into account the variabilities of causal relations across individuals/groups and leverages their commonalities to achieve statistically reliable estimation.
Proceedings Article
Fault Tolerance in Iterative-Convergent Machine Learning
TL;DR: A general framework is developed to quantify the effects of calculation errors on iterative-convergent algorithms and use this framework to design new strategies for checkpoint-based fault tolerance, which yields a worst-case upper bound on the iteration cost of arbitrary perturbations to model parameters during training.
Proceedings Article
The human kernel
TL;DR: In this paper, a kernel learning framework is proposed to reverse engineer the inductive biases of human learners across a set of behavioral experiments, and they use the learned kernels to gain psychological insights and to extrapolate in humanlike ways that go beyond traditional stationary and polynomial kernels.
Journal ArticleDOI
Spectrum: joint Bayesian inference of population structure and recombination events.
Kyung-Ah Sohn,Eric P. Xing +1 more
TL;DR: Spectrum offers an alternative view of the population structures to that offered by Structure 2.1, which ignores chromosome-level mutation and recombination with respect to founders, and generates an ancestral spectrum for representing population structures.