Prashant Khanduri
15 papers · 2021–2026 · 8 venues · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (36) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver 𧬠Topic Evolution
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Renaissance Researcher
(5)
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Research topics
Artificial Intelligence
(9)
Machine Learning
(9)
Core AI
(7)
Optimization & Theory Β· Machine Learning
(7)
Deep Learning
(4)
Mathematics & Optimization
(4)
Learning Types
(4)
Optimization
(4)
Computer Vision
(3)
Learning Paradigms Β· Artificial Intelligence
(3)
Application Areas
(2)
Domain-Specific
(2)
Learning Paradigms Β· Machine Learning
(2)
Optimization & Theory Β· Deep Learning
(2)
Processing
(2)
Keywords
federated learning
(4)
bilevel optimization
(4)
sample complexity
(2)
medical image segmentation
(2)
stochastic gradient
(2)
communication complexity
(2)
stochastic optimization
(2)
computed tomography
(2)
neural network
(2)
convergence analysis
(2)
robust optimization
(1)
adversarial learning
(1)
depth estimation
(1)
visual grounding
(1)
distributed optimization
(1)
robust classification
(1)
decentralized optimization
(1)
preference optimization
(1)
machine unlearning
(1)
adversarial training
(1)
Papers
Defeating Slow-and-Low Threats via Diffusion Model-based Generative Inference
NSDI 2026
Not All Tokens Are Meant to Be Forgotten
AAAI 2026
WalkGPT: Grounded Vision-Language Conversation with Depth-Aware Segmentation for Pedestrian Navigation
CVPR 2026
AutoProSAM: Automated Prompting SAM for 3D Multi-Organ Segmentation
WACV 2025
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training
WACV 2025
Fairness-aware Vision Transformer via Debiased Self-Attention
ECCV 2024
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation
ICML 2024
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks
ICML 2023
Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach
ICML 2023
Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning
ICML 2023
Anarchic Federated Learning
ICML 2022
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach
ICLR 2022
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization
ICML 2022
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum
NeurIPS 2021
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning
NeurIPS 2021