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03/20/2023
Learning Multi-Stage Multi-Grained Semantic Embeddings for E-Commerce Search
Retrieving relevant items that match users' queries from billion-scale c...
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08/12/2022
Pre-training Tasks for User Intent Detection and Embedding Retrieval in E-commerce Search
BERT-style models pre-trained on the general corpus (e.g., Wikipedia) an...
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06/27/2020
Learning Optimal Tree Models Under Beam Search
Retrieving relevant targets from an extremely large target set under com...
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02/01/2019
Understanding MCMC Dynamics as Flows on the Wasserstein Space
It is known that the Langevin dynamics used in MCMC is the gradient flow...
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07/04/2018
Accelerated First-order Methods on the Wasserstein Space for Bayesian Inference
We consider doing Bayesian inference by minimizing the KL divergence on ...
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12/07/2017
Learning Random Fourier Features by Hybrid Constrained Optimization
The kernel embedding algorithm is an important component for adapting ke...
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11/13/2017
Analyzing and Improving Stein Variational Gradient Descent for High-dimensional Marginal Inference
Stein variational gradient descent (SVGD) is a nonparametric inference m...
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08/16/2017