| 2023 |
Feature Learning in Deep Classifiers through Intermediate Neural Collapse ICML 2023 with Marius Lindegaard, Tomer Galanti and Tomaso Poggio
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| 2023 |
Dynamics in Deep Classifiers trained with the Square Loss: normalization, low rank, neural collapse and generalization bounds RESEARCH with Mengjia Xu, Tomer Galanti, Qianli Liao and Tomaso Poggio
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| 2023 |
For Interpolating Kernel Machines, Minimizing the Norm of the ERM Solution Maximizes Stability [pdf] Analysis and Applications 20th Anniversary Special Issue with Lorenzo Rosasco and Tomaso Poggio
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| 2022 |
Neural Collapse in Deep Homogeneous Classifiers and The Role of Weight Decay IEEE ICASSP 2022 with Andrzej Banburski-Fahey
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| 2021 |
A Scale Invariant Flatness Measure for Deep Network Minima IEEE ICASSP 2021 with Nam H. Nguyen, Abhishek Kumar, Dzung Phan, Sang H. Chin, Trac D. Tran
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| 2019 |
Target Tracking and Classification Using Compressive Sensing Camera for SWIR Videos Signal Image and Video Processing with Chiman Kwan, Bryan Chou, Jonathan Yang, Trac Tran, Jack Zhang, Ralph Etienne-Cummings
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| 2018 |
Reconstruction-free Deep Convolutional Neural Networks for Partially Observed Images IEEE GlobalSIP 2018 with Arun Nair, Luoluo Liu, Sang H. Chin, Muyinatu A. Lediju Bell and Trac D. Tran
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| 2018 |
ChieF : A Change Pattern based Interpretable Failure Analyzer IEEE Big Data 2018 with Dhaval Patel, Lam Nguyen, Shrey Srivastava, and Jayant Kalagnanam
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| 2018 |
Sparse Coding and Autoencoders (arXiv) [pdf] IEEE ISIT 2018 with Anirbit Mukherjee, Amitabh Basu, Trac D. Tran, Sang H. Chin
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| 2018 |
A Greedy Pursuit Algorithm for Separating Signals from Nonlinear Compressive Observations IEEE ICASSP 2018 with Dung Tran, Trac D. Tran, Sang H. Chin
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| 2016 |
Predicting Local Field Potentials with Recurrent Neural Networks IEEE EMBC 2016 with Louis Kim, Jacob Harer, Sang H. Chin, et. al.
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| 2015 |
Targeted Dot Product Representation for Friend Recommendation in Online Social Networks IEEE/ACM ASONAM 2015 with Minh Dao, Nam P. Nguyen, Trac D. Tran, Sang H. Chin
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