149 citations · 414 across the 15 of their papers we have counts for
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Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers
Jianbo Ye, Xin Lu, Zhe Lin +1
Model pruning has become a useful technique that improves the computational efficiency of deep learning, making it possible to deploy solutions in resource-limited scenarios. A wid…
Active Learning of Strict Partial Orders: A Case Study on Concept Prerequisite Relations
Chen Liang, Jianbo Ye, Han Zhao +2
Strict partial order is a mathematical structure commonly seen in relational data. One obstacle to extracting such type of relations at scale is the lack of large-scale labels for…
Aggregated Wasserstein Metric and State Registration for Hidden Markov Models
Yukun Chen, Jianbo Ye, Jia Li
We propose a framework, named Aggregated Wasserstein, for computing a dissimilarity measure or distance between two Hidden Markov Models with state conditional distributions being…
A Distance for HMMs based on Aggregated Wasserstein Metric and State Registration
Yukun Chen, Jianbo Ye, Jia Li
We propose a framework, named Aggregated Wasserstein, for computing a dissimilarity measure or distance between two Hidden Markov Models with state conditional distributions being…
Multiple Closed-Form Local Metric Learning for K-Nearest Neighbor Classifier
Jianbo Ye
Many researches have been devoted to learn a Mahalanobis distance metric, which can effectively improve the performance of kNN classification. Most approaches are iterative and com…