160 citations · 659 across the 33 of their papers we have counts for
4 papers · 1 filter
Regularization via Adaptive Pairwise Label Smoothing
Hongyu Guo
Label Smoothing (LS) is an effective regularizer to improve the generalization of state-of-the-art deep models. For each training sample the LS strategy smooths the one-hot encoded…
On SkipGram Word Embedding Models with Negative Sampling: Unified Framework and Impact of Noise Distributions
Dezhi Liu, Richong Zhang, Ziqiao Wang
SkipGram word embedding models with negative sampling, or SGN in short, is an elegant family of word embedding models. In this paper, we formulate a framework for word embedding, r…
A Graph to Graphs Framework for Retrosynthesis Prediction
Chence Shi, Minkai Xu, Hongyu Guo +2
A fundamental problem in computational chemistry is to find a set of reactants to synthesize a target molecule, a.k.a. retrosynthesis prediction. Existing state-of-the-art methods…
Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers
Masoumeh Soflaei, Hongyu Guo, Ali Al-Bashabsheh +2
We consider the problem of learning a neural network classifier. Under the information bottleneck (IB) principle, we associate with this classification problem a representation lea…