Varun Kanade
34 papers · 2009–2024 · 9 conferences · across top CS/AI conferences
Achievements
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🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (13) 🐣 Hot Topic Early Bird
🗺️
Taxonomy Completionist
(13)
🧭
Keyword Pioneer
🌍
Conference Polyglot
(9)
🏆
Keyword Champion
(2)
🔬
Deep Specialist
(12)
🗃️
Keyword Collector
(54)
📈
Trend Setter
🔥
Unstoppable
(8)
⚡
Prolific Year
(5)
❓
The Questioner
(2)
💎
Century Club
(34)
Conferences
NIPS (16)
COLT (5)
AISTATS (4)
ICLR (2)
ICML (2)
JMLR (2)
ACL (1)
ALT (1)
IJCAI (1)
Top co-authors
Keywords
regret bound
(5)
sample complexity
(4)
online learning
(4)
robust learning
(3)
regret minimization
(3)
adversarial learning
(3)
multi-armed bandit
(3)
pac learning
(3)
kernel methods
(3)
computational complexity
(3)
stochastic block model
(2)
transformer architecture
(2)
query complexity
(2)
distribution-free learning
(2)
adversarial attack
(2)
gradient descent
(2)
learning theory
(2)
graph embedding
(2)
distributed learning
(2)
robust classification
(2)
Papers
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions
ICLR 2024
Separations in the Representational Capabilities of Transformers and Recurrent Architectures
NIPS 2024
Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition
JMLR 2024
Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions
ACL 2023
Partial Matrix Completion
NIPS 2023
Sample Complexity Bounds for Robustly Learning Decision Lists against Evasion Attacks
IJCAI 2022
When are Local Queries Useful for Robust Learning?
NIPS 2022
Efficient Learning with Arbitrary Covariate Shift
ALT 2021
How Benign is Benign Overfitting ?
ICLR 2021
On the Hardness of Robust Classification
JMLR 2021
Towards optimally abstaining from prediction with OOD test examples
NIPS 2021
Online k-means Clustering
AISTATS 2021
Differentiable Causal Backdoor Discovery
AISTATS 2020
The Statistical Complexity of Early-Stopped Mirror Descent
NIPS 2020
Adaptive Reduced Rank Regression
NIPS 2020
Implicit Regularization for Optimal Sparse Recovery
NIPS 2019
Statistical Windows in Testing for the Initial Distribution of a Reversible Markov Chain
AISTATS 2019
Decentralized Cooperative Stochastic Bandits
NIPS 2019
On the Hardness of Robust Classification
NIPS 2019
Clustering Redemption–Beyond the Impossibility of Kleinberg’s Axioms
NIPS 2018
TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service
ICML 2018
Online Optimization of Smoothed Piecewise Constant Functions
AISTATS 2017
From which world is your graph
NIPS 2017
Hierarchical Clustering Beyond the Worst-Case
NIPS 2017
Reliably Learning the ReLU in Polynomial Time
COLT 2017
MCMC Learning
COLT 2015
Distribution-independent Reliable Learning
COLT 2014
Tracking Adversarial Targets
ICML 2014
Online Learning in Markov Decision Processes with Adversarially Chosen Transition Probability Distributions
NIPS 2013
Learning Using Local Membership Queries
COLT 2013
Computational Bounds on Statistical Query Learning
COLT 2012
Distributed Non-Stochastic Experts
NIPS 2012
Efficient Learning of Generalized Linear and Single Index Models with Isotonic Regression
NIPS 2011
Potential-Based Agnostic Boosting
NIPS 2009