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Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints


Sep 09, 2021
Zichao Wang, Andrew S. Lan, Richard G. Baraniuk

* EMNLP 2021 

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A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning


Sep 06, 2021
Yehuda Dar, Vidya Muthukumar, Richard G. Baraniuk


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The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization


Jun 14, 2021
Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk

* 19 pages, 2 figures. Submitted to NeurIPS 2021 

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NePTuNe: Neural Powered Tucker Network for Knowledge Graph Completion


Apr 15, 2021
Shashank Sonkar, Arzoo Katiyar, Richard G. Baraniuk


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Extreme Compressed Sensing of Poisson Rates from Multiple Measurements


Mar 15, 2021
Pavan K. Kota, Daniel LeJeune, Rebekah A. Drezek, Richard G. Baraniuk

* 21 pages, 7 figures 

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Transfer Learning Can Outperform the True Prior in Double Descent Regularization


Mar 09, 2021
Yehuda Dar, Richard G. Baraniuk


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Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels


Oct 27, 2020
Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, Richard G. Baraniuk


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Diagnostic Questions:The NeurIPS 2020 Education Challenge


Aug 03, 2020
Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang

* 28 pages, 6 figures, NeurIPS 2020 Competition Track 

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Ensembles of Generative Adversarial Networks for Disconnected Data


Jun 25, 2020
Lorenzo Luzi, Randall Balestriero, Richard G. Baraniuk


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An Improved Semi-Supervised VAE for Learning Disentangled Representations


Jun 22, 2020
Weili Nie, Zichao Wang, Ankit B. Patel, Richard G. Baraniuk


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Analytical Probability Distributions and EM-Learning for Deep Generative Networks


Jun 17, 2020
Randall Balestriero, Sebastien Paris, Richard G. Baraniuk


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Interpretable Super-Resolution via a Learned Time-Series Representation


Jun 13, 2020
Randall Balestriero, Herve Glotin, Richard G. Baraniuk


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LaRVAE: Label Replacement VAE for Semi-Supervised Disentanglement Learning


Jun 12, 2020
Weili Nie, Zichao Wang, Ankit B. Patel, Richard G. Baraniuk


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Double Double Descent: On Generalization Errors in Transfer Learning between Linear Regression Tasks


Jun 12, 2020
Yehuda Dar, Richard G. Baraniuk


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MomentumRNN: Integrating Momentum into Recurrent Neural Networks


Jun 12, 2020
Tan M. Nguyen, Richard G. Baraniuk, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang

* 23 pages, 9 figures 

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Attention Word Embedding


Jun 01, 2020
Shashank Sonkar, Andrew E. Waters, Richard G. Baraniuk


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qDKT: Question-centric Deep Knowledge Tracing


May 25, 2020
Shashank Sonkar, Andrew E. Waters, Andrew S. Lan, Phillip J. Grimaldi, Richard G. Baraniuk


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Deep Learning Techniques for Inverse Problems in Imaging


May 12, 2020
Gregory Ongie, Ajil Jalal, Christopher A. Metzler, Richard G. Baraniuk, Alexandros G. Dimakis, Rebecca Willett


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Subspace Fitting Meets Regression: The Effects of Supervision and Orthonormality Constraints on Double Descent of Generalization Errors


Feb 25, 2020
Yehuda Dar, Paul Mayer, Lorenzo Luzi, Richard G. Baraniuk


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Scheduled Restart Momentum for Accelerated Stochastic Gradient Descent


Feb 24, 2020
Bao Wang, Tan M. Nguyen, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher

* 20 pages, 13 figures, 15 tables 

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InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers


Dec 09, 2019
Tan M. Nguyen, Animesh Garg, Richard G. Baraniuk, Anima Anandkumar

* 17 pages, 14 figures, 2 tables 

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The Implicit Regularization of Ordinary Least Squares Ensembles


Oct 10, 2019
Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk

* 21 pages, 4 figures 

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Drawing early-bird tickets: Towards more efficient training of deep networks


Sep 26, 2019
Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Yingyan Lin, Zhangyang Wang, Richard G. Baraniuk


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Out-of-Distribution Detection Using Neural Rendering Generative Models


Jul 10, 2019
Yujia Huang, Sihui Dai, Tan Nguyen, Richard G. Baraniuk, Anima Anandkumar


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IdeoTrace: A Framework for Ideology Tracing with a Case Study on the 2016 U.S. Presidential Election


May 30, 2019
Indu Manickam, Andrew S. Lan, Gautam Dasarathy, Richard G. Baraniuk

* 9 pages, 4 figures, submitted to ASONAM 2019 

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Thresholding Graph Bandits with GrAPL


May 22, 2019
Daniel LeJeune, Gautam Dasarathy, Richard G. Baraniuk

* 15 pages, 3 figures 

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RACE: Sub-Linear Memory Sketches for Approximate Near-Neighbor Search on Streaming Data


Apr 09, 2019
Benjamin Coleman, Anshumali Shrivastava, Richard G. Baraniuk


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Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks


Feb 27, 2019
Joshua J. Michalenko, Ameesh Shah, Abhinav Verma, Richard G. Baraniuk, Swarat Chaudhuri, Ankit B. Patel

* 15 Pages, 13 Figures, Accepted to ICLR 2019 

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