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Detecting Foodborne Illness Complaints in Multiple Languages Using English Annotations Only

Oct 11, 2020
Ziyi Liu, Giannis Karamanolakis, Daniel Hsu, Luis Gravano

* Accepted for the 11th International Workshop on Health Text Mining and Information Analysis ([email protected] 2020) 

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Cross-Lingual Text Classification with Minimal Resources by Transferring a Sparse Teacher

Oct 06, 2020
Giannis Karamanolakis, Daniel Hsu, Luis Gravano

* Accepted to Findings of EMNLP 2020 (Long Paper) 

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On the proliferation of support vectors in high dimensions

Sep 22, 2020
Daniel Hsu, Vidya Muthukumar, Ji Xu


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Contrastive learning, multi-view redundancy, and linear models

Aug 24, 2020
Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu


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Statistical Query Lower Bounds for Tensor PCA

Aug 10, 2020
Rishabh Dudeja, Daniel Hsu


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Ensuring Fairness Beyond the Training Data

Jul 12, 2020
Debmalya Mandal, Samuel Deng, Suman Jana, Jeannette M. Wing, Daniel Hsu

* 18 pages, 3 figures 

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Classification vs regression in overparameterized regimes: Does the loss function matter?

May 16, 2020
Vidya Muthukumar, Adhyyan Narang, Vignesh Subramanian, Mikhail Belkin, Daniel Hsu, Anant Sahai


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Contrastive estimation reveals topic posterior information to linear models

Mar 04, 2020
Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu


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A New Framework for Query Efficient Active Imitation Learning

Dec 30, 2019
Daniel Hsu


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Weakly Supervised Attention Networks for Fine-Grained Opinion Mining and Public Health

Sep 30, 2019
Giannis Karamanolakis, Daniel Hsu, Luis Gravano

* Accepted for the 5th Workshop on Noisy User-generated Text (W-NUT 2019), held in conjunction with EMNLP 2019 

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Privacy Accounting and Quality Control in the Sage Differentially Private ML Platform

Sep 06, 2019
Mathias Lecuyer, Riley Spahn, Kiran Vodrahalli, Roxana Geambasu, Daniel Hsu

* Extended version of a paper presented at the 27th ACM Symposium on Operating Systems Principles (SOSP '19) 

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Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training

Sep 01, 2019
Giannis Karamanolakis, Daniel Hsu, Luis Gravano

* Accepted to EMNLP 2019 

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Unbiased estimators for random design regression

Jul 08, 2019
Michał Dereziński, Manfred K. Warmuth, Daniel Hsu


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A gradual, semi-discrete approach to generative network training via explicit Wasserstein minimization

Jun 11, 2019
Yucheng Chen, Matus Telgarsky, Chao Zhang, Bolton Bailey, Daniel Hsu, Jian Peng

* Appears in ICML 2019 

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A cryptographic approach to black box adversarial machine learning

Jun 07, 2019
Kevin Shi, Daniel Hsu, Allison Bishop


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Diameter-based Interactive Structure Search

Jun 05, 2019
Christopher Tosh, Daniel Hsu

* Presented at 2019 ICML Workshop on Human in the Loop Learning (HILL 2019), Long Beach, USA 

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How many variables should be entered in a principal component regression equation?

Jun 04, 2019
Ji Xu, Daniel Hsu


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Two models of double descent for weak features

Mar 18, 2019
Mikhail Belkin, Daniel Hsu, Ji Xu


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Reconciling modern machine learning and the bias-variance trade-off

Dec 28, 2018
Mikhail Belkin, Daniel Hsu, Siyuan Ma, Soumik Mandal


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Benefits of over-parameterization with EM

Oct 26, 2018
Ji Xu, Daniel Hsu, Arian Maleki

* Accepted at NIPS 2018 

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Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate

Oct 26, 2018
Mikhail Belkin, Daniel Hsu, Partha Mitra


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Multi-period Time Series Modeling with Sparsity via Bayesian Variational Inference

Oct 23, 2018
Daniel Hsu


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Certified Robustness to Adversarial Examples with Differential Privacy

Oct 07, 2018
Mathias Lecuyer, Vaggelis Atlidakis, Roxana Geambasu, Daniel Hsu, Suman Jana


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Leveraged volume sampling for linear regression

Sep 05, 2018
Michał Dereziński, Manfred K. Warmuth, Daniel Hsu


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Non-Gaussian information from weak lensing data via deep learning

May 01, 2018
Arushi Gupta, Jos├ę Manuel Zorrilla Matilla, Daniel Hsu, Zolt├ín Haiman

* Phys. Rev. D 97, 103515 (2018) 
* 15 pages, 13 figures, accepted to PRD 

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Linear regression without correspondence

Nov 07, 2017
Daniel Hsu, Kevin Shi, Xiaorui Sun


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Anomaly Detection on Graph Time Series

Nov 01, 2017
Daniel Hsu


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Mixing time estimation in reversible Markov chains from a single sample path

Aug 24, 2017
Daniel Hsu, Aryeh Kontorovich, David A. Levin, Yuval Peres, Csaba Szepesvári

* 34 pages, merges results of arXiv:1506.02903 and arXiv:1612.05330 

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Time Series Compression Based on Adaptive Piecewise Recurrent Autoencoder

Aug 16, 2017
Daniel Hsu

* arXiv admin note: text overlap with arXiv:1707.00666 

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