← Authors

Aarti Singh

69 papers · 2008–2026 · 10 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (28) 🧭 Keyword Pioneer 🌍 Conference Polyglot (10) 🐝 Cross-Pollinator (13) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (17) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🏠 Conference Loyalist (21) 🌟 Keyword Trendsetter Combo (5) 🀝 Dynamic Duo (13) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ† Keyword Champion πŸ† Grand Slam 🌱 Topic Pioneer πŸ”¬ Deep Specialist (20) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (16) ⚑ Prolific Year (5) πŸ’Ž Century Club (68) πŸ—ƒοΈ Keyword Collector (105) ❓ The Questioner

Conferences

NIPS (21) AISTATS (20) ICML (12) JMLR (6) AAAI (3) COLT (2) ICLR (2) ALT (1) EACL (1) UAI (1)

Top co-authors

Yining Wang (13) Sivaraman Balakrishnan (11) BarnabΓ‘s PΓ³czos (9) Larry Wasserman (8) Yichong Xu (6) Alessandro Rinaldo (6) Artur Dubrawski (6) Aaditya Ramdas (5) Ivan Stelmakh (5) Yuanzhi Li (5)

Research topics

Statistics (3) Differential Privacy (1) Education (1)

Keywords

sample complexity (6) active learning (5) pairwise comparison (4) convolutional neural network (4) combinatorial optimization (3) convergence rate (3) learning theory (3) subspace clustering (3) multi-armed bandit (3) matrix completion (3) gradient descent (3) high-dimensional statistics (3) nonparametric regression (3) regret bound (3) semi-supervised learning (3) statistical learning (3) hypothesis testing (3) statistical testing (3) non-convex optimization (3) zeroth-order optimization (3)

Papers

Scaling Up AI Alignment AAAI 2026
Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects ICML 2025
Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect AISTATS 2025
Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF ICML 2025
Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect ICML 2025
Learning Social Welfare Functions NIPS 2024
Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs ICLR 2024
Hybrid Reinforcement Learning from Offline Observation Alone ICML 2024
Goodhart’s Law Applies to NLP’s Explanation Benchmarks EACL 2024
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage NIPS 2024
The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms ICML 2023
Adaptation to Misspecified Kernel Regularity in Kernelised Bandits AISTATS 2023
Weighted Tallying Bandits: Overcoming Intractability via Repeated Exposure Optimality ICML 2023
Two-Sample Testing on Ranked Preference Data and the Role of Modeling Assumptions JMLR 2022
Complete Policy Regret Bounds for Tallying Bandits COLT 2022
A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences AAAI 2021
Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment AAAI 2021
Smooth Bandit Optimization: Generalization to Holder Space AISTATS 2021
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review JMLR 2021
Local Signal Adaptivity: Provable Feature Learning in Neural Networks Beyond Kernels NIPS 2021
Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information JMLR 2020
Preference-based Reinforcement Learning with Finite-Time Guarantees NIPS 2020
Zeroth Order Non-convex optimization with Dueling-Choice Bandits UAI 2020
Thresholding Bandit Problem with Both Duels and Pulls AISTATS 2020
PeerReview4All: Fair and Accurate Reviewer Assignment in Peer Review ALT 2019
On Testing for Biases in Peer Review NIPS 2019
Gradient Descent Provably Optimizes Over-parameterized Neural Networks ICLR 2019
Towards Understanding the Generalization Bias of Two Layer Convolutional Linear Classifiers with Gradient Descent AISTATS 2019
How Many Samples are Needed to Estimate a Convolutional Neural Network? NIPS 2018
Nonparametric Regression with Comparisons: Escaping the Curse of Dimensionality with Ordinal Information ICML 2018
Gradient Descent Learns One-hidden-layer CNN: Don’t be Afraid of Spurious Local Minima ICML 2018
Stochastic Zeroth-order Optimization in High Dimensions AISTATS 2018
Provably Correct Algorithms for Matrix Column Subset Selection with Selectively Sampled Data JMLR 2018
Optimization of Smooth Functions with Noisy Observations: Local Minimax Rates NIPS 2018
Near-Optimal Design of Experiments via Regret Minimization ICML 2017
Gradient Descent Can Take Exponential Time to Escape Saddle Points NIPS 2017
Uncorrelation and Evenness: a New Diversity-Promoting Regularizer ICML 2017
Hypothesis Transfer Learning via Transformation Functions NIPS 2017
Noise-Tolerant Interactive Learning Using Pairwise Comparisons NIPS 2017
On the Power of Truncated SVD for General High-rank Matrix Estimation Problems NIPS 2017
Computationally Efficient Robust Sparse Estimation in High Dimensions COLT 2017
On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models JMLR 2017
Graph Connectivity in Noisy Sparse Subspace Clustering AISTATS 2016
Active Learning Algorithms for Graphical Model Selection AISTATS 2016
Data Poisoning Attacks on Factorization-Based Collaborative Filtering NIPS 2016
Column Subset Selection with Missing Data via Active Sampling AISTATS 2015
Differentially private subspace clustering NIPS 2015
Efficient Sparse Clustering of High-Dimensional Non-spherical Gaussian Mixtures AISTATS 2015
On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives AISTATS 2015
A Deterministic Analysis of Noisy Sparse Subspace Clustering for Dimensionality-reduced Data ICML 2015
FuSSO: Functional Shrinkage and Selection Operator AISTATS 2014
An Analysis of Active Learning with Uniform Feature Noise AISTATS 2014
Changepoint Detection over Graphs with the Spectral Scan Statistic AISTATS 2013
Detecting Activations over Graphs using Spanning Tree Wavelet Bases AISTATS 2013
Distribution-Free Distribution Regression AISTATS 2013
Cluster Trees on Manifolds NIPS 2013
Optimal rates for stochastic convex optimization under Tsybakov noise condition ICML 2013
Low-Rank Matrix and Tensor Completion via Adaptive Sampling NIPS 2013
Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation NIPS 2013
Near-optimal Anomaly Detection in Graphs using Lovasz Extended Scan Statistic NIPS 2013
Sparsistency of the Edge Lasso over Graphs AISTATS 2012
Minimax rates for homology inference AISTATS 2012
Stability of Density-Based Clustering JMLR 2012
Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities AISTATS 2011
Noise Thresholds for Spectral Clustering NIPS 2011
Minimax Localization of Structural Information in Large Noisy Matrices NIPS 2011
Detecting Weak but Hierarchically-Structured Patterns in Networks AISTATS 2010
Identifying graph-structured activation patterns in networks NIPS 2010
Unlabeled data: Now it helps, now it doesn't NIPS 2008