Vijayaraghavan, Aravindan

27 publications

COLT 2025 Agnostic Learning of Arbitrary ReLU Activation Under Gaussian Marginals Anxin Guo, Aravindan Vijayaraghavan

COLT 2025 Computing High-Dimensional Confidence Sets for Arbitrary Distributions Chao Gao, Liren Shan, Vaidehi Srinivas, Aravindan Vijayaraghavan

NeurIPS 2025 Guarantees for Alternating Least Squares in Overparameterized Tensor Decompositions Dionysis Arvanitakis, Vaidehi Srinivas, Aravindan Vijayaraghavan

ICML 2025 Volume Optimality in Conformal Prediction with Structured Prediction Sets Chao Gao, Liren Shan, Vaidehi Srinivas, Aravindan Vijayaraghavan

NeurIPS 2024 Theoretical Analysis of Weak-to-Strong Generalization Hunter Lang, David Sontag, Aravindan Vijayaraghavan

ICLR 2023 Agnostic Learning of General ReLU Activation Using Gradient Descent Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan

ALT 2022 Algorithms for Learning a Mixture of Linear Classifiers Aidao Chen, Anindya De, Aravindan Vijayaraghavan

NeurIPS 2022 The Burer-Monteiro SDP Method Can Fail Even Above the Barvinok-Pataki Bound Liam O'Carroll, Vaidehi Srinivas, Aravindan Vijayaraghavan

NeurIPS 2022 Training Subset Selection for Weak Supervision Hunter Lang, Aravindan Vijayaraghavan, David Sontag

ALT 2022 Understanding Simultaneous Train and Test Robustness Pranjal Awasthi, Sivaraman Balakrishnan, Aravindan Vijayaraghavan

AISTATS 2021 Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances Hunter Lang, Aravind Reddy, David Sontag, Aravindan Vijayaraghavan

COLT 2021 Adversarially Robust Low Dimensional Representations Pranjal Awasthi, Vaggos Chatziafratis, Xue Chen, Aravindan Vijayaraghavan

NeurIPS 2021 Efficient Algorithms for Learning Depth-2 Neural Networks with General ReLU Activations Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan

ICML 2021 Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch) Hunter Lang, David Sontag, Aravindan Vijayaraghavan

ALT 2021 Learning a Mixture of Two Subspaces over Finite Fields Aidao Chen, Anindya De, Aravindan Vijayaraghavan

NeurIPS 2020 Adversarial Robustness via Robust Low Rank Representations Pranjal Awasthi, Himanshu Jain, Ankit Singh Rawat, Aravindan Vijayaraghavan

COLT 2020 Estimating Principal Components Under Adversarial Perturbations Pranjal Awasthi, Xue Chen, Aravindan Vijayaraghavan

AISTATS 2019 Block Stability for MAP Inference Hunter Lang, David Sontag, Aravindan Vijayaraghavan

NeurIPS 2019 On Robustness to Adversarial Examples and Polynomial Optimization Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan

ICML 2018 Clustering Semi-Random Mixtures of Gaussians Aravindan Vijayaraghavan, Pranjal Awasthi

AISTATS 2018 Optimality of Approximate Inference Algorithms on Stable Instances Hunter Lang, David A. Sontag, Aravindan Vijayaraghavan

NeurIPS 2017 Clustering Stable Instances of Euclidean K-Means. Aravindan Vijayaraghavan, Abhratanu Dutta, Alex Wang

COLT 2016 Learning Communities in the Presence of Errors Konstantin Makarychev, Yury Makarychev, Aravindan Vijayaraghavan

COLT 2015 Correlation Clustering with Noisy Partial Information Konstantin Makarychev, Yury Makarychev, Aravindan Vijayaraghavan

NeurIPS 2014 Learning Mixtures of Ranking Models Pranjal Awasthi, Avrim Blum, Or Sheffet, Aravindan Vijayaraghavan

COLT 2014 Open Problem: Tensor Decompositions: Algorithms up to the Uniqueness Threshold? Aditya Bhaskara, Moses Charikar, Ankur Moitra, Aravindan Vijayaraghavan

COLT 2014 Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability Aditya Bhaskara, Moses Charikar, Aravindan Vijayaraghavan