Soumik Sarkar
13 papers · 2017–2025 · 8 venues · across top CS/AI venues
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Deep Learning
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Machine Learning
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Reinforcement Learning
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Core AI
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Learning Types Β· Deep Learning
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conditional generation
(2)
adversarial attack
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decentralized learning
(2)
zero-shot learning
(2)
federated learning
(2)
deep reinforcement learning
(2)
distributed training
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generative model
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sample complexity
(2)
continual learning
(1)
image generation
(1)
offline reinforcement learning
(1)
online learning
(1)
sim-to-real transfer
(1)
reinforcement learning
(1)
few-shot learning
(1)
image segmentation
(1)
image classification
(1)
in-context learning
(1)
gradient-based optimization
(1)
Papers
Latent Safety-Constrained Policy Approach for Safe Offline Reinforcement Learning
ICLR 2025
Leveraging Vision Language Models for Specialized Agricultural Tasks
WACV 2025
Zero-shot Sim-to-Real Transfer for Reinforcement Learning-based Visual Servoing of Soft Continuum Arms
L4DC 2025
BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity
NeurIPS 2024
DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models
CVPR 2024
MDPGT: Momentum-Based Decentralized Policy Gradient Tracking
AAAI 2022
Cross-Gradient Aggregation for Decentralized Learning from Non-IID Data
ICML 2021
Differentiable Spline Approximations
NeurIPS 2021
InvNet: Encoding Geometric and Statistical Invariances in Deep Generative Models
AAAI 2020
Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents
AAAI 2020
Semantic Adversarial Attacks: Parametric Transformations That Fool Deep Classifiers
ICCV 2019
Online Robust Policy Learning in the Presence of Unknown Adversaries
NeurIPS 2018
Collaborative Deep Learning in Fixed Topology Networks
NeurIPS 2017