Soham De

Orcid: 0000-0001-7907-1335

According to our database1, Soham De authored at least 46 papers between 2011 and 2024.

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Bibliography

2024
Networks and Influencers in Online Propaganda Events: A Comparative Study of Three Cases in India.
Proc. ACM Hum. Comput. Interact., 2024

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models.
CoRR, 2024

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.
CoRR, 2024

Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
ConvNets Match Vision Transformers at Scale.
CoRR, 2023

Unlocking Accuracy and Fairness in Differentially Private Image Classification.
CoRR, 2023

On the Universality of Linear Recurrences Followed by Nonlinear Projections.
CoRR, 2023

Differentially Private Diffusion Models Generate Useful Synthetic Images.
CoRR, 2023

Resurrecting Recurrent Neural Networks for Long Sequences.
Proceedings of the International Conference on Machine Learning, 2023

2022
Unlocking High-Accuracy Differentially Private Image Classification through Scale.
CoRR, 2022

Closed Ranks: The Discursive Value of Military Support for Indian Politicians on Social Media.
CoRR, 2022

Database of Indian Social Media Influencers on Twitter.
CoRR, 2022

Regularising for invariance to data augmentation improves supervised learning.
CoRR, 2022

DISMISS: Database of Indian Social Media Influencers on Twitter.
Proceedings of the Sixteenth International AAAI Conference on Web and Social Media, 2022

Note: Picking Sides: The influencer-driven #HijabBan discourse on Twitter.
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.
CoRR, 2021

Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error.
CoRR, 2021

High-Performance Large-Scale Image Recognition Without Normalization.
Proceedings of the 38th International Conference on Machine Learning, 2021

On the Origin of Implicit Regularization in Stochastic Gradient Descent.
Proceedings of the 9th International Conference on Learning Representations, 2021

Characterizing signal propagation to close the performance gap in unnormalized ResNets.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
BYOL works even without batch statistics.
CoRR, 2020

Batch Normalization Biases Deep Residual Networks Towards Shallow Paths.
CoRR, 2020

Modeling Citation Trajectories of Scientific Papers.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020

Batch Normalization Biases Residual Blocks Towards the Identity Function in Deep Networks.
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.
Proceedings of the 37th International Conference on Machine Learning, 2020

The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Efficient Neural Network Verification with Exactness Characterization.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Adversarial Robustness through Local Linearization.
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.
PhD thesis, 2018

Convergence guarantees for RMSProp and ADAM in non-convex optimization and their comparison to Nesterov acceleration on autoencoders.
CoRR, 2018

Tipping Points for Norm Change in Human Cultures.
Proceedings of the Social, Cultural, and Behavioral Modeling, 2018

2017
Understanding Norm Change: An Evolutionary Game-Theoretic Approach (Extended Version).
CoRR, 2017

Training Quantized Nets: A Deeper Understanding.
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.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Understanding Norm Change: An Evolutionary Game-Theoretic Approach.
Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017

Automated Inference with Adaptive Batches.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Big Batch SGD: Automated Inference using Adaptive Batch Sizes.
CoRR, 2016

Using Game Theory to Study the Evolution of Cultural Norms.
CoRR, 2016

An Empirical Study of ADMM for Nonconvex Problems.
CoRR, 2016

Efficient Distributed SGD with Variance Reduction.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

resMBS: Constructing a Financial Supply Chain from Prospectus.
Proceedings of the Second International Workshop on Data Science for Macro-Modeling, 2016

2015
Scaling Up Distributed Stochastic Gradient Descent Using Variance Reduction.
CoRR, 2015

Variance Reduction for Distributed Stochastic Gradient Descent.
CoRR, 2015

Layer-Specific Adaptive Learning Rates for Deep Networks.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

2012
Plagiarism Detection in Polyphonic Music using Monaural Signal Separation.
Proceedings of the 13th Annual Conference of the International Speech Communication Association, 2012

2011
An improved fuzzy clustering method using modified Fukuyama-Sugeno cluster validity index.
Proceedings of the International Conference on Recent Trends in Information Systems, 2011


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