120 citations · 203 across the 7 of their papers we have counts for
7 papers
Extreme Multi-label Classification from Aggregated Labels
Yanyao Shen, Hsiang-fu Yu, Sujay Sanghavi +1
Extreme multi-label classification (XMC) is the problem of finding the relevant labels for an input, from a very large universe of possible labels. We consider XMC in the setting w…
Interaction Hard Thresholding: Consistent Sparse Quadratic Regression in Sub-quadratic Time and Space
Shuo Yang, Yanyao Shen, Sujay Sanghavi
Quadratic regression involves modeling the response as a (generalized) linear function of not only the features but also of quadratic terms . The inclusio…
Iterative Least Trimmed Squares for Mixed Linear Regression
Yanyao Shen, Sujay Sanghavi
Given a linear regression setting, Iterative Least Trimmed Squares (ILTS) involves alternating between (a) selecting the subset of samples with lowest current loss, and (b) re-fitt…
Learning with Bad Training Data via Iterative Trimmed Loss Minimization
Yanyao Shen, Sujay Sanghavi
In this paper, we study a simple and generic framework to tackle the problem of learning model parameters when a fraction of the training samples are corrupted. We first make a sim…
Dense Information Flow for Neural Machine Translation
Yanyao Shen, Xu Tan, Di He +2
Recently, neural machine translation has achieved remarkable progress by introducing well-designed deep neural networks into its encoder-decoder framework. From the optimization pe…
High Dimensional Robust Sparse Regression
Liu Liu, Yanyao Shen, Tianyang Li +1
We provide a novel -- and to the best of our knowledge, the first -- algorithm for high dimensional sparse regression with constant fraction of corruptions in explanatory and/or re…
Deep Active Learning for Named Entity Recognition
Yanyao Shen, Hyokun Yun, Zachary C. Lipton +2
Deep learning has yielded state-of-the-art performance on many natural language processing tasks including named entity recognition (NER). However, this typically requires large am…