Source Themes

HOBIT: Hardness Optimized Batching for InfoNCE Training

Mining ard negatives using ANNS index is prohibtively epewnsive for industry scale datasets; we propose HOBIT tat reorders batches to provide mutually informative in-batch negatives.

Himanshu Dutta, Lokesh Nagalapatti, Yashoteja Prabhu

From Search to Sampling: Generative Models for Robust Algorithmic Recourse

We propose a generative model for recourse that outputs a distribution over likely recourse instances.

Prateek Garg, Lokesh Nagalapatti, Sunita Sarawagi

Robust Root Cause Diagnosis using In-Distribution Interventions

Identifying root cause of anomalies using interventions rather estimated from a learned SCM

Lokesh Nagalapatti, Ashutosh Srivastava, Sunita Sarawagi, Amit Sharma

Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE

Estimating CATE from post-treatment covariates leveraging a simulator that generates synthetic counterfactuals.

Lokesh Nagalapatti, Pranava Singhal (=), Avishek Ghosh, Sunita Sarawagi

Tab-Shapley: Identifying Top-k Tabular Data Quality Insights

Identifying group anomalies (covering both columns and rows) in Tabular Data using Game theoretic models.

Manisha Padala, Lokesh Nagalapatti, Atharv Tyagi, Ramasuri Narayanam, Shiv Kumar Saini

Continuous Treatment Effect estimation using Gradient Interpolation and Kernel Smoothing

A two-pronged strategy to infer treatment effects for continuous treatments.

Lokesh Nagalapatti, Akshay Iyer, Abir De, Sunita Sarawagi

Gradient Coresets for Federated Learning

Finding coresets in federated learning.

Durga Sivasubramanian (=), Lokesh Nagalapatti, Rishabh Iyer, Ganesh Ramakrishnan

PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect

A simple loss on pairs of observational instances outperforms (almost) SOTA approaches on Treatment Effect Estimation

Lokesh Nagalapatti, Pranava Singhal (=), Avishek Ghosh, Sunita Sarawagi

Generating task-specific training data

Generating training datasets specific to a downstream ML task.

Lokesh Nagalapatti, Ramasuri Narayanam, Ruhi Sharma Mittal, Sambaran Bandyopadhyay

Last updated on Aug 26, 2023

Learning Recourse on Instance Environment to Enhance Prediction Accuracy

Learning recourse on the environment that generates data instances.

Lokesh Nagalapatti, Guntakanti Sai Koushik, Abir De, Sunita Sarawagi