← Authors

Aditya Bhaskara

28 papers · 2014–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (10) πŸ—ΊοΈ Taxonomy Completionist (14) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (11) 🧬 Topic Evolution πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (112) ⚑ Prolific Year (5) πŸ’Ž Century Club (28) πŸ“ˆ Trend Setter ❓ The Questioner

Conferences

NIPS (10) ICML (7) AISTATS (5) COLT (3) ALT (1) ICLR (1) JMLR (1)

Top co-authors

Ashok Cutkosky (6) Ravi Kumar (6) Manish Purohit (6) Vahab Mirrokni (3) Maheshakya Wijewardena (3) Aravinda Kanchana Ruwanpathirana (3) Morteza Zadimoghaddam (3) Moses Charikar (2) Aravindan Vijayaraghavan (2) Kamesh Munagala (2)

Keywords

regret bound (6) approximation algorithm (5) online linear optimization (4) online learning (4) k-means clustering (4) greedy algorithm (3) approximation guarantee (2) mixture model (2) linear optimization (2) online algorithm (2) logarithmic regret (2) matrix factorization (2) distributed algorithm (2) k-center clustering (2) community detection (2) distributed clustering (2) outlier detection (2) matrix approximation (2) stochastic block model (2) optimistic regret (2)

Papers

Descent with Misaligned Gradients and Applications to Hidden Convexity ICLR 2025
Convergence Guarantees for the DeepWalk Embedding on Block Models ICML 2024
On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models NIPS 2024
Structure of Nonlinear Node Embeddings in Stochastic Block Models AISTATS 2023
Tight Bounds for Volumetric Spanners and Applications NIPS 2023
Competing against Adaptive Strategies in Online Learning via Hints AISTATS 2023
Bandit Online Linear Optimization with Hints and Queries ICML 2023
Additive Error Guarantees for Weighted Low Rank Approximation ICML 2021
Power of Hints for Online Learning with Movement Costs AISTATS 2021
Principal Component Regression with Semirandom Observations via Matrix Completion AISTATS 2021
Logarithmic Regret from Sublinear Hints NIPS 2021
Robust Algorithms for Online $k$-means Clustering ALT 2020
Online Learning with Imperfect Hints ICML 2020
Adaptive Probing Policies for Shortest Path Routing NIPS 2020
Online Linear Optimization with Many Hints NIPS 2020
Online MAP Inference of Determinantal Point Processes NIPS 2020
Approximate Guarantees for Dictionary Learning COLT 2019
On Distributed Averaging for Stochastic k-PCA NIPS 2019
Greedy Sampling for Approximate Clustering in the Presence of Outliers NIPS 2019
On Binary Embedding using Circulant Matrices JMLR 2018
Distributed Clustering via LSH Based Data Partitioning ICML 2018
Linear Relaxations for Finding Diverse Elements in Metric Spaces NIPS 2016
Greedy Column Subset Selection: New Bounds and Distributed Algorithms ICML 2016
Sparse Solutions to Nonnegative Linear Systems and Applications AISTATS 2015
Provable Bounds for Learning Some Deep Representations ICML 2014
Open Problem: Tensor Decompositions: Algorithms up to the Uniqueness Threshold? COLT 2014
Distributed Balanced Clustering via Mapping Coresets NIPS 2014
Uniqueness of Tensor Decompositions with Applications to Polynomial Identifiability COLT 2014