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ORCIDSoham De
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Books and Theses
- 2018
[b1]Soham De:
Fast optimization methods for machine learning, and game-theoretic models of cultural evolution. University of Maryland, College Park, MD, USA, 2018
Journal Articles
- 2024
- [j1]Anirban Sen
, Soham De, Joyojeet Pal:
Networks and Influencers in Online Propaganda Events: A Comparative Study of Three Cases in India. Proc. ACM Hum. Comput. Interact. 8(CSCW1): 1-27 (2024)
Conference and Workshop Papers
- 2024
- [c23]Antonio Orvieto, Soham De, Caglar Gulcehre, Razvan Pascanu, Samuel L. Smith:
Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues. ICML 2024 - 2023
- [c22]Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, Çaglar Gülçehre, Razvan Pascanu, Soham De:
Resurrecting Recurrent Neural Networks for Long Sequences. ICML 2023: 26670-26698 - 2022
- [c21]Soham De, Anmol Panda, Joyojeet Pal:
Note: Picking Sides: The influencer-driven #HijabBan discourse on Twitter. COMPASS 2022: 556-559 - [c20]Arshia Arya, Soham De, Dibyendu Mishra, Gazal Shekhawat, Ankur Sharma, Anmol Panda, Faisal M. Lalani, Parantak Singh, Ramaravind Kommiya Mothilal, Rynaa Grover, Sachita Nishal, Saloni Dash, Shehla Rashid Shora, Syeda Zainab Akbar, Joyojeet Pal:
DISMISS: Database of Indian Social Media Influencers on Twitter. ICWSM 2022: 1201-1207 - 2021
- [c19]Andrew Brock, Soham De, Samuel L. Smith:
Characterizing signal propagation to close the performance gap in unnormalized ResNets. ICLR 2021 - [c18]Samuel L. Smith, Benoit Dherin, David G. T. Barrett, Soham De:
On the Origin of Implicit Regularization in Stochastic Gradient Descent. ICLR 2021 - [c17]Andy Brock, Soham De, Samuel L. Smith, Karen Simonyan:
High-Performance Large-Scale Image Recognition Without Normalization. ICML 2021: 1059-1071 - 2020
- [c16]Karthik Abinav Sankararaman, Soham De, Zheng Xu, W. Ronny Huang, Tom Goldstein:
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent. ICML 2020: 8469-8479 - [c15]Samuel L. Smith, Erich Elsen, Soham De:
On the Generalization Benefit of Noise in Stochastic Gradient Descent. ICML 2020: 9058-9067 - [c14]Soham De, Samuel L. Smith:
Batch Normalization Biases Residual Blocks Towards the Identity Function in Deep Networks. NeurIPS 2020 - [c13]Dattatreya Mohapatra, Siddharth Pal, Soham De, Ponnurangam Kumaraguru, Tanmoy Chakraborty:
Modeling Citation Trajectories of Scientific Papers. PAKDD (2) 2020: 620-632 - 2019
- [c12]Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli:
Adversarial Robustness through Local Linearization. NeurIPS 2019: 13824-13833 - [c11]Krishnamurthy (Dj) Dvijotham, Robert Stanforth, Sven Gowal, Chongli Qin, Soham De, Pushmeet Kohli:
Efficient Neural Network Verification with Exactness Characterization. UAI 2019: 497-507 - 2018
- [c10]Soham De, Dana S. Nau, Xinyue Pan, Michele J. Gelfand:
Tipping Points for Norm Change in Human Cultures. SBP-BRiMS 2018: 61-69 - 2017
- [c9]Soham De, Abhay Kumar Yadav, David W. Jacobs, Tom Goldstein:
Automated Inference with Adaptive Batches. AISTATS 2017: 1504-1513 - [c8]Soham De, Dana S. Nau, Michele J. Gelfand:
Understanding Norm Change: An Evolutionary Game-Theoretic Approach. AAMAS 2017: 1433-1441 - [c7]Carlos Domingo Castillo, Soham De, Xintong Han, Bharat Singh, Abhay Kumar Yadav, Tom Goldstein:
Son of Zorn's lemma: Targeted style transfer using instance-aware semantic segmentation. ICASSP 2017: 1348-1352 - [c6]Hao Li, Soham De, Zheng Xu, Christoph Studer, Hanan Samet, Tom Goldstein:
Training Quantized Nets: A Deeper Understanding. NIPS 2017: 5811-5821 - 2016
- [c5]Douglas Burdick, Soham De, Louiqa Raschid, Mingchao Shao, Zheng Xu, Elena Zotkina:
resMBS: Constructing a Financial Supply Chain from Prospectus. DSMM@SIGMOD 2016: 7:1-7:6 - [c4]Soham De, Tom Goldstein:
Efficient Distributed SGD with Variance Reduction. ICDM 2016: 111-120 - 2015
- [c3]Bharat Singh, Soham De, Yangmuzi Zhang, Thomas A. Goldstein, Gavin Taylor:
Layer-Specific Adaptive Learning Rates for Deep Networks. ICMLA 2015: 364-368 - 2012
- [c2]Soham De, Indradyumna Roy, Tarunima Prabhakar, Kriti Suneja, Sourish Chaudhuri, Rita Singh, Bhiksha Raj:
Plagiarism Detection in Polyphonic Music using Monaural Signal Separation. INTERSPEECH 2012: 1744-1747 - 2011
- [c1]Sailik Sengupta, Soham De, Amit Konar, Ramadoss Janarthanan:
An improved fuzzy clustering method using modified Fukuyama-Sugeno cluster validity index. ReTIS 2011: 269-274
Informal and Other Publications
- 2024
- [i34]Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev, George-Cristian Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, Arnaud Doucet, David Budden, Yee Whye Teh, Razvan Pascanu, Nando de Freitas, Caglar Gulcehre:
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. CoRR abs/2402.19427 (2024) - [i33]Aleksandar Botev, Soham De, Samuel L. Smith, Anushan Fernando, George-Cristian Muraru, Ruba Haroun, Leonard Berrada, Razvan Pascanu, Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret, Sertan Girgin, Olivier Bachem, Alek Andreev, Kathleen Kenealy, Thomas Mesnard, Cassidy Hardin, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, Pouya Tafti, Armand Joulin, Noah Fiedel, Evan Senter, Yutian Chen, Srivatsan Srinivasan, Guillaume Desjardins, David Budden, Arnaud Doucet, Sharad Vikram, Adam Paszke, Trevor Gale, Sebastian Borgeaud, Charlie Chen, Andy Brock, Antonia Paterson, Jenny Brennan, Meg Risdal, Raj Gundluru, Nesh Devanathan, Paul Mooney, Nilay Chauhan, Phil Culliton, Luiz GUStavo Martins, Elisa Bandy, David Huntsperger, Glenn Cameron, Arthur Zucker, Tris Warkentin, Ludovic Peran, Minh Giang, Zoubin Ghahramani, Clément Farabet, Koray Kavukcuoglu, Demis Hassabis, Raia Hadsell, Yee Whye Teh, Nando de Frietas:
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models. CoRR abs/2404.07839 (2024) - 2023
- [i32]Sahra Ghalebikesabi, Leonard Berrada, Sven Gowal, Ira Ktena, Robert Stanforth, Jamie Hayes, Soham De, Samuel L. Smith, Olivia Wiles, Borja Balle:
Differentially Private Diffusion Models Generate Useful Synthetic Images. CoRR abs/2302.13861 (2023) - [i31]Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, Çaglar Gülçehre, Razvan Pascanu, Soham De:
Resurrecting Recurrent Neural Networks for Long Sequences. CoRR abs/2303.06349 (2023) - [i30]Antonio Orvieto, Soham De, Çaglar Gülçehre, Razvan Pascanu, Samuel L. Smith:
On the Universality of Linear Recurrences Followed by Nonlinear Projections. CoRR abs/2307.11888 (2023) - [i29]Leonard Berrada, Soham De, Judy Hanwen Shen, Jamie Hayes, Robert Stanforth, David Stutz, Pushmeet Kohli, Samuel L. Smith, Borja Balle:
Unlocking Accuracy and Fairness in Differentially Private Image Classification. CoRR abs/2308.10888 (2023) - [i28]Samuel L. Smith, Andrew Brock, Leonard Berrada, Soham De:
ConvNets Match Vision Transformers at Scale. CoRR abs/2310.16764 (2023) - 2022
- [i27]Aleksander Botev, Matthias Bauer, Soham De:
Regularising for invariance to data augmentation improves supervised learning. CoRR abs/2203.03304 (2022) - [i26]Arshia Arya, Soham De, Dibyendu Mishra, Gazal Shekhawat, Ankur Sharma, Anmol Panda, Faisal M. Lalani, Parantak Singh, Ramaravind Kommiya Mothilal, Rynaa Grover, Sachita Nishal, Saloni Dash, Shehla Rashid Shora, Syeda Zainab Akbar, Joyojeet Pal:
Database of Indian Social Media Influencers on Twitter. CoRR abs/2203.09193 (2022) - [i25]Agrima Seth, Soham De, Arshia Arya, Steven Wilkinson, Sushant Singh, Joyojeet Pal:
Closed Ranks: The Discursive Value of Military Support for Indian Politicians on Social Media. CoRR abs/2204.03098 (2022) - [i24]Soham De, Leonard Berrada, Jamie Hayes, Samuel L. Smith, Borja Balle:
Unlocking High-Accuracy Differentially Private Image Classification through Scale. CoRR abs/2204.13650 (2022) - 2021
- [i23]Andrew Brock, Soham De, Samuel L. Smith:
Characterizing signal propagation to close the performance gap in unnormalized ResNets. CoRR abs/2101.08692 (2021) - [i22]Samuel L. Smith, Benoit Dherin, David G. T. Barrett, Soham De:
On the Origin of Implicit Regularization in Stochastic Gradient Descent. CoRR abs/2101.12176 (2021) - [i21]Andrew Brock, Soham De, Samuel L. Smith, Karen Simonyan:
High-Performance Large-Scale Image Recognition Without Normalization. CoRR abs/2102.06171 (2021) - [i20]Stanislav Fort, Andrew Brock, Razvan Pascanu, Soham De, Samuel L. Smith:
Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error. CoRR abs/2105.13343 (2021) - [i19]Tudor Berariu, Wojciech Czarnecki, Soham De, Jörg Bornschein, Samuel L. Smith, Razvan Pascanu, Claudia Clopath:
A study on the plasticity of neural networks. CoRR abs/2106.00042 (2021) - 2020
- [i18]Dattatreya Mohapatra, Siddharth Pal, Soham De, Ponnurangam Kumaraguru, Tanmoy Chakraborty:
Modeling Citation Trajectories of Scientific Papers. CoRR abs/2002.06628 (2020) - [i17]Soham De, Samuel L. Smith:
Batch Normalization Biases Deep Residual Networks Towards Shallow Paths. CoRR abs/2002.10444 (2020) - [i16]Samuel L. Smith, Erich Elsen, Soham De:
On the Generalization Benefit of Noise in Stochastic Gradient Descent. CoRR abs/2006.15081 (2020) - [i15]Pierre H. Richemond, Jean-Bastien Grill, Florent Altché, Corentin Tallec, Florian Strub, Andrew Brock, Samuel L. Smith, Soham De, Razvan Pascanu, Bilal Piot, Michal Valko:
BYOL works even without batch statistics. CoRR abs/2010.10241 (2020) - 2019
- [i14]Karthik Abinav Sankararaman, Soham De, Zheng Xu, W. Ronny Huang, Tom Goldstein:
The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent. CoRR abs/1904.06963 (2019) - [i13]Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli:
Adversarial Robustness through Local Linearization. CoRR abs/1907.02610 (2019) - 2018
- [i12]Soham De, Dana S. Nau, Xinyue Pan, Michele J. Gelfand:
Tipping Points for Norm Change in Human Cultures. CoRR abs/1804.07406 (2018) - [i11]Amitabh Basu, Soham De, Anirbit Mukherjee, Enayat Ullah:
Convergence guarantees for RMSProp and ADAM in non-convex optimization and their comparison to Nesterov acceleration on autoencoders. CoRR abs/1807.06766 (2018) - 2017
- [i10]Carlos Domingo Castillo, Soham De, Xintong Han, Bharat Singh, Abhay Kumar Yadav, Tom Goldstein:
Son of Zorn's Lemma: Targeted Style Transfer Using Instance-aware Semantic Segmentation. CoRR abs/1701.02357 (2017) - [i9]Soham De, Dana S. Nau, Michele J. Gelfand:
Understanding Norm Change: An Evolutionary Game-Theoretic Approach (Extended Version). CoRR abs/1704.04720 (2017) - [i8]Hao Li, Soham De, Zheng Xu, Christoph Studer, Hanan Samet, Tom Goldstein:
Training Quantized Nets: A Deeper Understanding. CoRR abs/1706.02379 (2017) - 2016
- [i7]Soham De, Dana S. Nau, Michele Gelfand:
Using Game Theory to Study the Evolution of Cultural Norms. CoRR abs/1606.02570 (2016) - [i6]Soham De, Abhay Kumar Yadav, David W. Jacobs, Tom Goldstein:
Big Batch SGD: Automated Inference using Adaptive Batch Sizes. CoRR abs/1610.05792 (2016) - [i5]Zheng Xu, Soham De, Mário A. T. Figueiredo, Christoph Studer, Tom Goldstein:
An Empirical Study of ADMM for Nonconvex Problems. CoRR abs/1612.03349 (2016) - 2015
- [i4]Soham De, Indradyumna Roy, Tarunima Prabhakar, Kriti Suneja, Sourish Chaudhuri, Rita Singh, Bhiksha Raj:
Plagiarism Detection in Polyphonic Music using Monaural Signal Separation. CoRR abs/1503.00022 (2015) - [i3]Bharat Singh, Soham De, Yangmuzi Zhang, Thomas A. Goldstein, Gavin Taylor:
Layer-Specific Adaptive Learning Rates for Deep Networks. CoRR abs/1510.04609 (2015) - [i2]Soham De, Gavin Taylor, Tom Goldstein:
Variance Reduction for Distributed Stochastic Gradient Descent. CoRR abs/1512.01708 (2015) - [i1]Soham De, Gavin Taylor, Tom Goldstein:
Scaling Up Distributed Stochastic Gradient Descent Using Variance Reduction. CoRR abs/1512.02970 (2015)
Coauthor Index
aka: Thomas A. Goldstein
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