Kartik Ahuja

According to our database1, Kartik Ahuja authored at least 47 papers between 2014 and 2024.

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Bibliography

2024
On Provable Length and Compositional Generalization.
CoRR, 2024

2023
Multi-Domain Causal Representation Learning via Weak Distributional Invariances.
CoRR, 2023

Context is Environment.
CoRR, 2023

Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection.
CoRR, 2023

A Closer Look at In-Context Learning under Distribution Shifts.
CoRR, 2023

Reusable Slotwise Mechanisms.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization.
Proceedings of the International Conference on Machine Learning, 2023

Why does Throwing Away Data Improve Worst-Group Error?
Proceedings of the International Conference on Machine Learning, 2023

Interventional Causal Representation Learning.
Proceedings of the International Conference on Machine Learning, 2023

2022
Recycling diverse models for out-of-distribution generalization.
CoRR, 2022

Empirical Study on Optimizer Selection for Out-of-Distribution Generalization.
CoRR, 2022

FL Games: A federated learning framework for distribution shifts.
CoRR, 2022

WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series Tasks.
CoRR, 2022

Weakly Supervised Representation Learning with Sparse Perturbations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Properties from mechanisms: an equivariance perspective on identifiable representation learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Towards efficient representation identification in supervised learning.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization.
CoRR, 2021

SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization.
CoRR, 2021

Conditionally independent data generation.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Adversarial Feature Desensitization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization?
Proceedings of the 38th International Conference on Machine Learning, 2021

Empirical or Invariant Risk Minimization? A Sample Complexity Perspective.
Proceedings of the 9th International Conference on Learning Representations, 2021

Treatment Effect Estimation Using Invariant Risk Minimization.
Proceedings of the IEEE International Conference on Acoustics, 2021

Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Dynamic Matching and Allocation of Tasks.
ACM Trans. Economics and Comput., 2020

Learning to Initialize Gradient Descent Using Gradient Descent.
CoRR, 2020

Invariant Risk Minimization Games.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Optimization Methods for Resource Allocation and Machine Learning Applications.
PhD thesis, 2019

Optimal Piecewise Approximations for Model Interpretation.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

Joint Concordance Index.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

Estimating Kullback-Leibler Divergence Using Kernel Machines.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
A Micro-Foundation of Social Capital in Evolving Social Networks.
IEEE Trans. Netw. Sci. Eng., 2018

Risk-Stratify: Confident Stratification Of Patients Based On Risk.
CoRR, 2018

Piecewise Approximations of Black Box Models for Model Interpretation.
CoRR, 2018

2017
DPSCREEN: Dynamic Personalized Screening.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Repeated Matching Mechanism Design with Moral Hazard and Adverse Selection.
CoRR, 2016

2015
Efficient Interference Management Policies for Femtocell Networks.
IEEE Trans. Wirel. Commun., 2015

Self-Organizing Networks of Information Gathering Cognitive Agents.
IEEE Trans. Cogn. Commun. Netw., 2015

The Population Dynamics of Websites: [Extended Abstract].
SIGMETRICS Perform. Evaluation Rev., 2015

Distributed Interference Management Policies for Heterogeneous Small Cell Networks.
IEEE J. Sel. Areas Commun., 2015

Evolution of Social Networks: A Microfounded Model.
CoRR, 2015

2014
To participate or not in spectrum auctions with entry fee: Bayesian game theoretic approach.
Proceedings of the IEEE Wireless Communications and Networking Conference, 2014

Spectrum sharing for delay-sensitive applications with continuing QoS guarantees.
Proceedings of the IEEE Global Communications Conference, 2014

Towards a theory of societal co-evolution: Individualism versus collectivism.
Proceedings of the 2014 IEEE Global Conference on Signal and Information Processing, 2014


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