Ramya Korlakai Vinayak

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 23

Top Topics

Preference Learning

Maximum Likelihood Estimation

Pairwise Comparison

Graph Clustering

Top Venues

Publications

Harrison Rosenberg, Shimaa Ahmed, Guruprasad V. Ramesh, Kassem Fawaz, Ramya Korlakai Vinayak
Limitations of Face Image Generation. AAAI (2024)
Daiwei Chen, Yi Chen, Aniket Rege, Ramya Korlakai Vinayak
PAL: Pluralistic Alignment Framework for Learning from Heterogeneous Preferences. CoRR (2024)
Gokcan Tatli, Yi Chen, Ramya Korlakai Vinayak
Learning Populations of Preferences via Pairwise Comparison Queries. AISTATS (2024)
Harit Vishwakarma, Heguang Lin, Ramya Korlakai Vinayak
Taming False Positives in Out-of-Distribution Detection with Human Feedback. CoRR (2024)
Harit Vishwakarma, Heguang Lin, Ramya Korlakai Vinayak
Taming False Positives in Out-of-Distribution Detection with Human Feedback. AISTATS (2024)
Zhi Wang, Geelon So, Ramya Korlakai Vinayak
Metric Learning from Limited Pairwise Preference Comparisons. CoRR (2024)
Harit Vishwakarma, Reid Chen, Sui Jiet Tay, Satya Sai Srinath Namburi, Frederic Sala, Ramya Korlakai Vinayak
Pearls from Pebbles: Improved Confidence Functions for Auto-labeling. CoRR (2024)
Harrison Rosenberg, Shimaa Ahmed, Guruprasad V. Ramesh, Ramya Korlakai Vinayak, Kassem Fawaz
Unbiased Face Synthesis With Diffusion Models: Are We There Yet? CoRR (2023)
Harit Vishwakarma, Heguang Lin, Frederic Sala, Ramya Korlakai Vinayak
Promises and Pitfalls of Threshold-based Auto-labeling. NeurIPS (2023)
Gregory Canal, Blake Mason, Ramya Korlakai Vinayak, Robert Nowak
One for All: Simultaneous Metric and Preference Learning over Multiple Users. NeurIPS (2022)
Harit Vishwakarma, Heguang Lin, Frederic Sala, Ramya Korlakai Vinayak
Good Data from Bad Models : Foundations of Threshold-based Auto-labeling. CoRR (2022)
Gokcan Tatli, Robert D. Nowak, Ramya Korlakai Vinayak
Learning Preference Distributions From Distance Measurements. Allerton (2022)
Gregory Canal, Blake Mason, Ramya Korlakai Vinayak, Robert D. Nowak
One for All: Simultaneous Metric and Preference Learning over Multiple Users. CoRR (2022)
Zhen Miao, Weihao Kong, Ramya Korlakai Vinayak, Wei Sun, Fang Han
Fisher-Pitman permutation tests based on nonparametric Poisson mixtures with application to single cell genomics. CoRR (2021)
Jennifer Brennan, Ramya Korlakai Vinayak, Kevin Jamieson
Estimating the number and effect sizes of non-null hypotheses. CoRR (2020)
Jennifer Brennan, Ramya Korlakai Vinayak, Kevin Jamieson
Estimating the Number and Effect Sizes of Non-null Hypotheses. ICML (2020)
Ramya Korlakai Vinayak, Weihao Kong, Sham M. Kakade
Optimal Estimation of Change in a Population of Parameters. CoRR (2019)
Ramya Korlakai Vinayak, Weihao Kong, Gregory Valiant, Sham M. Kakade
Maximum Likelihood Estimation for Learning Populations of Parameters. ICML (2019)
Ramya Korlakai Vinayak, Weihao Kong, Gregory Valiant, Sham M. Kakade
Maximum Likelihood Estimation for Learning Populations of Parameters. CoRR (2019)
Gabriel Cadamuro, Ramya Korlakai Vinayak, Joshua Blumenstock, Sham M. Kakade, Jacob Shapiro
The Illusion of Change: Correcting for Biases in Change Inference for Sparse, Societal-Scale Data. WWW (2019)
Ramya Korlakai Vinayak, Tijana Zrnic, Babak Hassibi
Tensor-based crowdsourced clustering via triangle queries. ICASSP (2017)
Ramya Korlakai Vinayak, Babak Hassibi
Similarity clustering in the presence of outliers: Exact recovery via convex program. ISIT (2016)
Ramya Korlakai Vinayak, Babak Hassibi
Crowdsourced Clustering: Querying Edges vs Triangles. NIPS (2016)
Ramya Korlakai Vinayak, Samet Oymak, Babak Hassibi
Sharp performance bounds for graph clustering via convex optimization. ICASSP (2014)
Ramya Korlakai Vinayak, Samet Oymak, Babak Hassibi
Graph Clustering With Missing Data: Convex Algorithms and Analysis. NIPS (2014)