Anup Rao
23 papers · 2015–2025 · 9 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (43) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π€
Dynamic Duo
(12)
ποΈ
Keyword Collector
(119)
π
Conference Pioneer
π₯
Unstoppable Β· Bronze
β‘
Prolific Year Β· Productive
π
Century Club Β· Bronze
π
Renaissance Researcher
(6)
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Trend Setter
Top co-authors
Research topics
Machine Learning
(19)
Optimization & Theory
(12)
Mathematics & Optimization
(9)
Core Methods
(8)
Optimization
(8)
Artificial Intelligence
(6)
Core AI
(6)
Learning Types Β· Machine Learning
(6)
Mathematics
(5)
Deep Learning
(4)
Application Areas
(3)
Natural Language Processing
(2)
Learning Types Β· Deep Learning
(2)
Computer Science
(1)
Knowledge & Reasoning
(1)
Keywords
causal inference
(5)
experimental design
(4)
average treatment effect
(3)
large language model
(2)
determinantal point process
(2)
compressed sensing
(1)
active learning
(1)
differential privacy
(1)
semi-supervised learning
(1)
graph-based optimization
(1)
model selection
(1)
online learning
(1)
convex optimization
(1)
graph clustering
(1)
robust optimization
(1)
ridge regression
(1)
text summarization
(1)
stochastic gradient descent
(1)
knowledge editing
(1)
graph theory
(1)
Papers
Evaluation and Incident Prevention in an Enterprise AI Assistant
AAAI 2025
On Distributional Discrepancy for Experimental Design with General Assignment Probabilities
AISTATS 2025
DeCoT: Debiasing Chain-of-Thought for Knowledge-Intensive Tasks in Large Language Models via Causal Intervention
ACL 2024
Hallucination Diversity-Aware Active Learning for Text Summarization
NAACL 2024
ReCON: Training-Free Acceleration for Text-to-Image Synthesis with Retrieval of Concept Prompt Trajectories
ECCV 2024
Optimal Sketching Bounds for Sparse Linear Regression
AISTATS 2023
Conditional Generative Model Based Predicate-Aware Query Approximation
AAAI 2022
One-Pass Algorithms for MAP Inference of Nonsymmetric Determinantal Point Processes
ICML 2022
Online Balanced Experimental Design
ICML 2022
Sample Constrained Treatment Effect Estimation
NeurIPS 2022
Asymptotics of Ridge Regression in Convolutional Models
ICML 2021
Coresets for Classification β Simplified and Strengthened
NeurIPS 2021
Designing Transportable Experiments Under S-admissability
AISTATS 2021
Efficient Balanced Treatment Assignments for Experimentation
AISTATS 2021
Fundamental Tradeoffs in Distributionally Adversarial Training
ICML 2021
Graph Neural Networks with Heterophily
AAAI 2021
Machine Unlearning via Algorithmic Stability
COLT 2021
Model Selection in Contextual Stochastic Bandit Problems
NeurIPS 2020
On Densification for Minwise Hashing
UAI 2019
Sample Efficient Graph-Based Optimization with Noisy Observations
AISTATS 2019
Algorithms for Lipschitz Learning on Graphs
COLT 2015
Fast, Provable Algorithms for Isotonic Regression in all L_p-norms
NeurIPS 2015
Stochastic Block Model and Community Detection in Sparse Graphs: A spectral algorithm with optimal rate of recovery
COLT 2015