Soham De

According to our database, Soham De authored at least 43 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.

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, Çaglar Gülçehre

CoRR, 2024

2023

ConvNets Match Vision Transformers at Scale.

Samuel L. Smith, Andrew Brock, Leonard Berrada, Soham De

CoRR, 2023

Unlocking Accuracy and Fairness in Differentially Private Image Classification.

Leonard Berrada, Soham De, Judy Hanwen Shen, Jamie Hayes, Robert Stanforth, David Stutz, Pushmeet Kohli, Samuel L. Smith, Borja Balle

CoRR, 2023

On the Universality of Linear Recurrences Followed by Nonlinear Projections.

Antonio Orvieto, Soham De, Çaglar Gülçehre, Razvan Pascanu, Samuel L. Smith

CoRR, 2023

Differentially Private Diffusion Models Generate Useful Synthetic Images.

Sahra Ghalebikesabi, Leonard Berrada, Sven Gowal, Ira Ktena, Robert Stanforth, Jamie Hayes, Soham De, Samuel L. Smith, Olivia Wiles, Borja Balle

CoRR, 2023

Resurrecting Recurrent Neural Networks for Long Sequences.

Antonio Orvieto, Samuel L. Smith, Albert Gu, Anushan Fernando, Çaglar Gülçehre, Razvan Pascanu, Soham De

Proceedings of the International Conference on Machine Learning, 2023

2022

Unlocking High-Accuracy Differentially Private Image Classification through Scale.

Soham De, Leonard Berrada, Jamie Hayes, Samuel L. Smith, Borja Balle

CoRR, 2022

Closed Ranks: The Discursive Value of Military Support for Indian Politicians on Social Media.

Agrima Seth, Soham De, Arshia Arya, Steven Wilkinson, Sushant Singh, Joyojeet Pal

CoRR, 2022

Database of Indian Social Media Influencers on Twitter.

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

CoRR, 2022

Regularising for invariance to data augmentation improves supervised learning.

Aleksander Botev, Matthias Bauer, Soham De

CoRR, 2022

DISMISS: Database of Indian Social Media Influencers on Twitter.

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

Proceedings of the Sixteenth International AAAI Conference on Web and Social Media, 2022

Note: Picking Sides: The influencer-driven #HijabBan discourse on Twitter.

Soham De, Anmol Panda, Joyojeet Pal

Proceedings of the COMPASS '22: ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies, Seattle, WA, USA, 29 June 2022, 2022

2021

A study on the plasticity of neural networks.

Tudor Berariu, Wojciech Czarnecki, Soham De, Jörg Bornschein, Samuel L. Smith, Razvan Pascanu, Claudia Clopath

CoRR, 2021

Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error.

Stanislav Fort, Andrew Brock, Razvan Pascanu, Soham De, Samuel L. Smith

CoRR, 2021

High-Performance Large-Scale Image Recognition Without Normalization.

Andy Brock, Soham De, Samuel L. Smith, Karen Simonyan

Proceedings of the 38th International Conference on Machine Learning, 2021

On the Origin of Implicit Regularization in Stochastic Gradient Descent.

Samuel L. Smith, Benoit Dherin, David G. T. Barrett, Soham De

Proceedings of the 9th International Conference on Learning Representations, 2021

Characterizing signal propagation to close the performance gap in unnormalized ResNets.

Andrew Brock, Soham De, Samuel L. Smith

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

BYOL works even without batch statistics.

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

CoRR, 2020

Batch Normalization Biases Deep Residual Networks Towards Shallow Paths.

Soham De, Samuel L. Smith

CoRR, 2020

Modeling Citation Trajectories of Scientific Papers.

Dattatreya Mohapatra, Siddharth Pal, Soham De, Ponnurangam Kumaraguru, Tanmoy Chakraborty

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Batch Normalization Biases Residual Blocks Towards the Identity Function in Deep Networks.

Soham De, Samuel L. Smith

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

On the Generalization Benefit of Noise in Stochastic Gradient Descent.

Samuel L. Smith, Erich Elsen, Soham De

Proceedings of the 37th International Conference on Machine Learning, 2020

The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent.

Karthik Abinav Sankararaman, Soham De, Zheng Xu, W. Ronny Huang, Tom Goldstein

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Efficient Neural Network Verification with Exactness Characterization.

Krishnamurthy (Dj) Dvijotham, Robert Stanforth, Sven Gowal, Chongli Qin, Soham De, Pushmeet Kohli

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Adversarial Robustness through Local Linearization.

Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Fast optimization methods for machine learning, and game-theoretic models of cultural evolution.

Soham De

PhD thesis, 2018

Convergence guarantees for RMSProp and ADAM in non-convex optimization and their comparison to Nesterov acceleration on autoencoders.

Amitabh Basu, Soham De, Anirbit Mukherjee, Enayat Ullah

CoRR, 2018

Tipping Points for Norm Change in Human Cultures.

Soham De, Dana S. Nau, Xinyue Pan, Michele J. Gelfand

Proceedings of the Social, Cultural, and Behavioral Modeling, 2018

2017

Understanding Norm Change: An Evolutionary Game-Theoretic Approach (Extended Version).

Soham De, Dana S. Nau, Michele J. Gelfand

CoRR, 2017

Training Quantized Nets: A Deeper Understanding.

Hao Li, Soham De, Zheng Xu, Christoph Studer, Hanan Samet, Tom Goldstein

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Son of Zorn's lemma: Targeted style transfer using instance-aware semantic segmentation.

Carlos Domingo Castillo, Soham De, Xintong Han, Bharat Singh, Abhay Kumar Yadav, Tom Goldstein

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Understanding Norm Change: An Evolutionary Game-Theoretic Approach.

Soham De, Dana S. Nau, Michele J. Gelfand

Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Automated Inference with Adaptive Batches.

Soham De, Abhay Kumar Yadav, David W. Jacobs, Tom Goldstein

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Big Batch SGD: Automated Inference using Adaptive Batch Sizes.

Soham De, Abhay Kumar Yadav, David W. Jacobs, Tom Goldstein

CoRR, 2016

Using Game Theory to Study the Evolution of Cultural Norms.

Soham De, Dana S. Nau, Michele Gelfand

CoRR, 2016

An Empirical Study of ADMM for Nonconvex Problems.

Zheng Xu, Soham De, Mário A. T. Figueiredo, Christoph Studer, Tom Goldstein

CoRR, 2016

Efficient Distributed SGD with Variance Reduction.

Soham De, Tom Goldstein

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

resMBS: Constructing a Financial Supply Chain from Prospectus.

Douglas Burdick, Soham De, Louiqa Raschid, Mingchao Shao, Zheng Xu, Elena Zotkina

Proceedings of the Second International Workshop on Data Science for Macro-Modeling, 2016

2015

Scaling Up Distributed Stochastic Gradient Descent Using Variance Reduction.

Soham De, Gavin Taylor, Tom Goldstein

CoRR, 2015

Variance Reduction for Distributed Stochastic Gradient Descent.

Soham De, Gavin Taylor, Tom Goldstein

CoRR, 2015

Layer-Specific Adaptive Learning Rates for Deep Networks.

Bharat Singh, Soham De, Yangmuzi Zhang, Thomas A. Goldstein, Gavin Taylor

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

2012

Plagiarism Detection in Polyphonic Music using Monaural Signal Separation.

Soham De, Indradyumna Roy, Tarunima Prabhakar, Kriti Suneja, Sourish Chaudhuri, Rita Singh, Bhiksha Raj

Proceedings of the INTERSPEECH 2012, 2012

2011

An improved fuzzy clustering method using modified Fukuyama-Sugeno cluster validity index.

Sailik Sengupta, Soham De, Amit Konar, Ramadoss Janarthanan

Proceedings of the International Conference on Recent Trends in Information Systems, 2011