Abhishek Sinha
14 papers · 2019–2026 · 10 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (31) π Academic Marathon Β· Sprint π Conference Polyglot Β· Gold π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Topic Evolution
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Keyword Champion
ποΈ
Keyword Collector
(60)
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Century Club Β· Bronze
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Unstoppable Β· Bronze
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Conference Pioneer
Venues
Top co-authors
Research topics
Machine Learning
(10)
Learning Types
(9)
Mathematics & Optimization
(6)
Optimization
(6)
Optimization & Theory
(6)
Deep Learning
(3)
Artificial Intelligence
(2)
Computer Science
(2)
Application Areas
(2)
Core Methods
(2)
Security & Privacy
(1)
Applications
(1)
Architectures
(1)
Bayesian & Probabilistic
(1)
Core AI
(1)
Keywords
regret bound
(4)
contrastive learning
(2)
multi-armed bandit
(2)
self-supervised learning
(2)
few-shot learning
(2)
adversarial attack
(2)
constraint violation
(2)
adversarial constraint
(2)
online convex optimization
(2)
representation learning
(2)
transfer learning
(1)
constrained optimization
(1)
dynamic regret
(1)
probability distribution
(1)
adversarial training
(1)
online learning
(1)
maximum mean discrepancy
(1)
conditional generation
(1)
online prediction
(1)
feature selection
(1)
Papers
Online Caching in Tree Networks: Algorithms, Regret, and Complexity
L4DC 2026
Universal Dynamic Regret and Constraint Violation Bounds for Constrained Online Convex Optimization
ALT 2026
BanditQ:Fair Bandits with Guaranteed Rewards
UAI 2024
Confidence Is All You Need for MI Attacks (Student Abstract)
AAAI 2024
Optimal Algorithms for Online Convex Optimization with Adversarial Constraints
NeurIPS 2024
No-regret Algorithms for Fair Resource Allocation
NeurIPS 2023
Comparing Distributions by Measuring Differences that Affect Decision Making
ICLR 2022
k-experts - Online Policies and Fundamental Limits
AISTATS 2022
LeadCache: Regret-Optimal Caching in Networks
NeurIPS 2021
D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation
NeurIPS 2021
Negative Data Augmentation
ICLR 2021
Attributional Robustness Training using Input-Gradient Spatial Alignment
ECCV 2020
Charting the Right Manifold: Manifold Mixup for Few-shot Learning
WACV 2020
Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models
IJCAI 2019