Goutham Rajendran

According to our database, Goutham Rajendran authored at least 19 papers between 2020 and 2024.

Collaborative distances:

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

2024

Do LLMs dream of elephants (when told not to)? Latent concept association and associative memory in transformers.

Yibo Jiang, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam

CoRR, 2024

Efficient Certificates of Anti-Concentration Beyond Gaussians.

Ainesh Bakshi, Pravesh Kothari, Goutham Rajendran, Madhur Tulsiani, Aravindan Vijayaraghavan

CoRR, 2024

Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models.

Goutham Rajendran, Simon Buchholz, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar

CoRR, 2024

On the Origins of Linear Representations in Large Language Models.

Yibo Jiang, Goutham Rajendran, Pradeep Kumar Ravikumar, Bryon Aragam, Victor Veitch

Proceedings of the Forty-first International Conference on Machine Learning, 2024

An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis.

Goutham Rajendran, Patrik Reizinger, Wieland Brendel, Pradeep Kumar Ravikumar

Proceedings of the Causal Learning and Reasoning, 2024

2023

Nonlinear Random Matrices and Applications to the Sum of Squares Hierarchy.

Goutham Rajendran

CoRR, 2023

Sum-of-Squares Lower Bounds for Densest k-Subgraph.

Chris Jones, Aaron Potechin, Goutham Rajendran, Jeff Xu

Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 2023

Concentration of polynomial random matrices via Efron-Stein inequalities.

Goutham Rajendran, Madhur Tulsiani

Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, 2023

Learning Linear Causal Representations from Interventions under General Nonlinear Mixing.

Simon Buchholz, Goutham Rajendran, Elan Rosenfeld, Bryon Aragam, Bernhard Schölkopf, Pradeep Ravikumar

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

2022

Analyzing Robustness of End-to-End Neural Models for Automatic Speech Recognition.

Goutham Rajendran, Wei Zou

CoRR, 2022

Combinatorial Optimization via the Sum of Squares Hierarchy.

Goutham Rajendran

CoRR, 2022

Identifiability of deep generative models under mixture priors without auxiliary information.

Bohdan Kivva, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam

CoRR, 2022

Sub-exponential time Sum-of-Squares lower bounds for Principal Components Analysis.

Aaron Potechin, Goutham Rajendran

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Identifiability of deep generative models without auxiliary information.

Bohdan Kivva, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families.

Goutham Rajendran, Bohdan Kivva, Ming Gao, Bryon Aragam

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

Learning latent causal graphs via mixture oracles.

Bohdan Kivva, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam

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

Sum-of-Squares Lower Bounds for Sparse Independent Set.

Chris Jones, Aaron Potechin, Goutham Rajendran, Madhur Tulsiani, Jeff Xu

Proceedings of the 62nd IEEE Annual Symposium on Foundations of Computer Science, 2021

2020

Machinery for Proving Sum-of-Squares Lower Bounds on Certification Problems.

Aaron Potechin, Goutham Rajendran

CoRR, 2020

Sum-of-Squares Lower Bounds for Sherrington-Kirkpatrick via Planted Affine Planes.

Mrinalkanti Ghosh, Fernando Granha Jeronimo, Chris Jones, Aaron Potechin, Goutham Rajendran

Proceedings of the 61st IEEE Annual Symposium on Foundations of Computer Science, 2020