Aravindan Vijayaraghavan
26 papers · 2014–2025 · 6 conferences · across top CS/AI conferences
Achievements
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Conferences
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NIPS (8)
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ALT (3)
ICML (3)
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Keywords
adversarial robustness
(4)
map inference
(4)
mixture model
(4)
tensor decomposition
(3)
learning theory
(3)
principal component analysis
(2)
neural network
(2)
k-means clustering
(2)
lp relaxation
(2)
combinatorial optimization
(2)
weak supervision
(2)
graph clustering
(2)
approximate inference
(2)
perturbation stability
(2)
computer vision
(1)
certified robustness
(1)
domain adaptation
(1)
semidefinite programming
(1)
semi-supervised learning
(1)
representation learning
(1)
Papers
Volume Optimality in Conformal Prediction with Structured Prediction Sets
ICML 2025
Agnostic Learning of Arbitrary ReLU Activation under Gaussian Marginals
COLT 2025
Computing High-dimensional Confidence Sets for Arbitrary Distributions
COLT 2025
Theoretical Analysis of Weak-to-Strong Generalization
NIPS 2024
Agnostic Learning of General ReLU Activation Using Gradient Descent
ICLR 2023
Algorithms for learning a mixture of linear classifiers
ALT 2022
Training Subset Selection for Weak Supervision
NIPS 2022
The Burer-Monteiro SDP method can fail even above the Barvinok-Pataki bound
NIPS 2022
Understanding Simultaneous Train and Test Robustness
ALT 2022
Adversarially Robust Low Dimensional Representations
COLT 2021
Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances
AISTATS 2021
Learning a mixture of two subspaces over finite fields
ALT 2021
Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch)
ICML 2021
Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations
NIPS 2021
Adversarial robustness via robust low rank representations
NIPS 2020
Estimating Principal Components under Adversarial Perturbations
COLT 2020
On Robustness to Adversarial Examples and Polynomial Optimization
NIPS 2019
Block Stability for MAP Inference
AISTATS 2019
Optimality of Approximate Inference Algorithms on Stable Instances
AISTATS 2018
Clustering Semi-Random Mixtures of Gaussians
ICML 2018
Clustering Stable Instances of Euclidean k-means.
NIPS 2017
Learning Communities in the Presence of Errors
COLT 2016
Correlation Clustering with Noisy Partial Information
COLT 2015
Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability
COLT 2014
Open Problem: Tensor Decompositions: Algorithms up to the Uniqueness Threshold?
COLT 2014
Learning Mixtures of Ranking Models
NIPS 2014