← Authors

Aravindan Vijayaraghavan

26 papers · 2014–2025 · 6 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (38) 🌍 Conference Polyglot (6) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (11) 🧭 Keyword Pioneer πŸ”₯ Unstoppable (12) ⚑ Prolific Year (5) πŸ’Ž Century Club (26) ❓ The Questioner πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (97)

Conferences

COLT (8) NIPS (8) AISTATS (3) ALT (3) ICML (3) ICLR (1)

Top co-authors

Pranjal Awasthi (9) David Sontag (6) Hunter Lang (6) Vaidehi Srinivas (3) Yury Makarychev (2) Konstantin Makarychev (2) Anindya De (2) Xue Chen (2) Moses Charikar (2) Abhratanu Dutta (2)

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