Kartik Ahuja

According to our database, Kartik Ahuja authored at least 51 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Compositional Risk Minimization.

Divyat Mahajan, Mohammad Pezeshki, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent

CoRR, 2024

Robust Data Pruning: Uncovering and Overcoming Implicit Bias.

Artem Vysogorets, Kartik Ahuja, Julia Kempe

CoRR, 2024

On Provable Length and Compositional Generalization.

Kartik Ahuja, Amin Mansouri

CoRR, 2024

Context is Environment.

Sharut Gupta, Stefanie Jegelka, David Lopez-Paz, Kartik Ahuja

Proceedings of the Twelfth International Conference on Learning Representations, 2024

On the Identifiability of Quantized Factors.

Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

Proceedings of the Causal Learning and Reasoning, 2024

Multi-Domain Causal Representation Learning via Weak Distributional Invariances.

Kartik Ahuja, Amin Mansouri, Yixin Wang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

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

Hiroki Naganuma, Kartik Ahuja, Shiro Takagi, Tetsuya Motokawa, Rio Yokota, Kohta Ishikawa, Ikuro Sato, Ioannis Mitliagkas

Trans. Mach. Learn. Res., 2023

WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series.

Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad-Javad Darvishi Bayazi, Pooneh Mousavi, Guillaume Dumas, Irina Rish

Trans. Mach. Learn. Res., 2023

Identifiability of Discretized Latent Coordinate Systems via Density Landmarks Detection.

Vitória Barin Pacela, Kartik Ahuja, Simon Lacoste-Julien, Pascal Vincent

CoRR, 2023

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

Kartik Ahuja, David Lopez-Paz

CoRR, 2023

Reusable Slotwise Mechanisms.

Trang Nguyen, Amin Mansouri, Kanika Madan, Khuong Nguyen, Kartik Ahuja, Dianbo Liu, Yoshua Bengio

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.

Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Kartik Ahuja, Vijay Arya

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.

Alexandre Ramé, Kartik Ahuja, Jianyu Zhang, Matthieu Cord, Léon Bottou, David Lopez-Paz

Proceedings of the International Conference on Machine Learning, 2023

Why does Throwing Away Data Improve Worst-Group Error?

Kamalika Chaudhuri, Kartik Ahuja, Martín Arjovsky, David Lopez-Paz

Proceedings of the International Conference on Machine Learning, 2023

Interventional Causal Representation Learning.

Kartik Ahuja, Divyat Mahajan, Yixin Wang, Yoshua Bengio

Proceedings of the International Conference on Machine Learning, 2023

2022

Recycling diverse models for out-of-distribution generalization.

Alexandre Ramé, Kartik Ahuja, Jianyu Zhang, Matthieu Cord, Léon Bottou, David Lopez-Paz

CoRR, 2022

FL Games: A Federated Learning Framework for Distribution Shifts.

Sharut Gupta, Kartik Ahuja, Mohammad Havaei, Niladri Chatterjee, Yoshua Bengio

CoRR, 2022

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

Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad-Javad Darvishi Bayazi, Guillaume Dumas, Irina Rish

CoRR, 2022

Weakly Supervised Representation Learning with Sparse Perturbations.

Kartik Ahuja, Jason S. Hartford, Yoshua Bengio

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.

Kartik Ahuja, Jason S. Hartford, Yoshua Bengio

Proceedings of the Tenth International Conference on Learning Representations, 2022

Towards efficient representation identification in supervised learning.

Kartik Ahuja, Divyat Mahajan, Vasilis Syrgkanis, Ioannis Mitliagkas

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge.

Abhin Shah, Karthikeyan Shanmugam, Kartik Ahuja

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

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

Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish

CoRR, 2021

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

Soroosh Shahtalebi, Jean-Christophe Gagnon-Audet, Touraj Laleh, Mojtaba Faramarzi, Kartik Ahuja, Irina Rish

CoRR, 2021

Conditionally independent data generation.

Kartik Ahuja, Prasanna Sattigeri, Karthikeyan Shanmugam, Dennis Wei, Karthikeyan Natesan Ramamurthy, Murat Kocaoglu

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Adversarial Feature Desensitization.

Pouya Bashivan, Reza Bayat, Adam Ibrahim, Kartik Ahuja, Mojtaba Faramarzi, Touraj Laleh, Blake A. Richards, Irina Rish

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.

Kartik Ahuja, Ethan Caballero, Dinghuai Zhang, Jean-Christophe Gagnon-Audet, Yoshua Bengio, Ioannis Mitliagkas, Irina Rish

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?

Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville

Proceedings of the 38th International Conference on Machine Learning, 2021

Empirical or Invariant Risk Minimization? A Sample Complexity Perspective.

Kartik Ahuja, Jun Wang, Amit Dhurandhar, Karthikeyan Shanmugam, Kush R. Varshney

Proceedings of the 9th International Conference on Learning Representations, 2021

Treatment Effect Estimation Using Invariant Risk Minimization.

Abhin Shah, Kartik Ahuja, Karthikeyan Shanmugam, Dennis Wei, Kush R. Varshney, Amit Dhurandhar

Proceedings of the IEEE International Conference on Acoustics, 2021

Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions.

Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Dynamic Matching and Allocation of Tasks.

Kartik Ahuja, Mihaela van der Schaar

ACM Trans. Economics and Comput., 2020

Learning to Initialize Gradient Descent Using Gradient Descent.

Kartik Ahuja, Amit Dhurandhar, Kush R. Varshney

CoRR, 2020

Invariant Risk Minimization Games.

Kartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney, Amit Dhurandhar

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Optimization Methods for Resource Allocation and Machine Learning Applications.

Kartik Ahuja

PhD thesis, 2019

Optimal Piecewise Approximations for Model Interpretation.

Kartik Ahuja, William R. Zame, Mihaela van der Schaar

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

Joint Concordance Index.

Kartik Ahuja, Mihaela van der Schaar

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

Estimating Kullback-Leibler Divergence Using Kernel Machines.

Kartik Ahuja

Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018

A Micro-Foundation of Social Capital in Evolving Social Networks.

Ahmed M. Alaa, Kartik Ahuja, Mihaela van der Schaar

IEEE Trans. Netw. Sci. Eng., 2018

Risk-Stratify: Confident Stratification Of Patients Based On Risk.

Kartik Ahuja, Mihaela van der Schaar

CoRR, 2018

Piecewise Approximations of Black Box Models for Model Interpretation.

Kartik Ahuja, William R. Zame, Mihaela van der Schaar

CoRR, 2018

2017

DPSCREEN: Dynamic Personalized Screening.

Kartik Ahuja, William R. Zame, Mihaela van der Schaar

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.

Kartik Ahuja, Mihaela van der Schaar

CoRR, 2016

2015

Efficient Interference Management Policies for Femtocell Networks.

Kartik Ahuja, Yuanzhang Xiao, Mihaela van der Schaar

IEEE Trans. Wirel. Commun., 2015

Self-Organizing Networks of Information Gathering Cognitive Agents.

Ahmed M. Alaa, Kartik Ahuja, Mihaela van der Schaar

IEEE Trans. Cogn. Commun. Netw., 2015

The Population Dynamics of Websites: [Extended Abstract].

Kartik Ahuja, Simpson Zhang, Mihaela van der Schaar

SIGMETRICS Perform. Evaluation Rev., 2015

Distributed Interference Management Policies for Heterogeneous Small Cell Networks.

Kartik Ahuja, Yuanzhang Xiao, Mihaela van der Schaar

IEEE J. Sel. Areas Commun., 2015

Evolution of Social Networks: A Microfounded Model.

Ahmed M. Alaa, Kartik Ahuja, Mihaela van der Schaar

CoRR, 2015

2014

To participate or not in spectrum auctions with entry fee: Bayesian game theoretic approach.

Kartik Ahuja, Mai H. Hassan, Md. Jahangir Hossain

Proceedings of the IEEE Wireless Communications and Networking Conference, 2014

Spectrum sharing for delay-sensitive applications with continuing QoS guarantees.

Yuanzhang Xiao, Kartik Ahuja, Mihaela van der Schaar

Proceedings of the IEEE Global Communications Conference, 2014

Towards a theory of societal co-evolution: Individualism versus collectivism.

Kartik Ahuja, Simpson Zhang, Mihaela van der Schaar

Proceedings of the 2014 IEEE Global Conference on Signal and Information Processing, 2014