Spencer Gordon

According to our database, Spencer Gordon authored at least 17 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of two.

2024

Two Choices Are Enough for P-LCPs, USOs, and Colorful Tangents.

Michaela Borzechowski, John Fearnley, Spencer Gordon, Rahul Savani, Patrick Schnider, Simon Weber

Proceedings of the 51st International Colloquium on Automata, Languages, and Programming, 2024

Identification of mixtures of discrete product distributions in near-optimal sample and time complexity.

Spencer L. Gordon, Erik Jahn, Bijan Mazaheri, Yuval Rabani, Leonard J. Schulman

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

Identifiability of Product of Experts Models.

Manav Kant, Eric Y. Ma, Andrei Staicu, Leonard J. Schulman, Spencer Gordon

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

2023

The Identification of Discrete Mixture Models.

Spencer Gordon

PhD thesis, 2023

Causal Discovery under Latent Class Confounding.

Bijan Mazaheri, Spencer Gordon, Yuval Rabani, Leonard J. Schulman

CoRR, 2023

Causal Inference Despite Limited Global Confounding via Mixture Models.

Spencer L. Gordon, Bijan Mazaheri, Yuval Rabani, Leonard J. Schulman

Proceedings of the Conference on Causal Learning and Reasoning, 2023

2022

Hadamard Extensions and the Identification of Mixtures of Product Distributions.

Spencer L. Gordon, Leonard J. Schulman

IEEE Trans. Inf. Theory, 2022

2021

Identifying Mixtures of Bayesian Network Distributions.

Spencer L. Gordon, Bijan Mazaheri, Yuval Rabani, Leonard J. Schulman

CoRR, 2021

On the computational equivalence of co-NP refutations of a matrix being a P-matrix.

Spencer Gordon, Kevin Shu

CoRR, 2021

Hadamard Powers and the Identification of Mixtures of Products.

Spencer L. Gordon, Leonard J. Schulman

CoRR, 2021

Condition number bounds for causal inference.

Spencer L. Gordon, Vinayak M. Kumar, Leonard J. Schulman, Piyush Srivastava

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

Source Identification for Mixtures of Product Distributions.

Spencer Gordon, Bijan H. Mazaheri, Yuval Rabani, Leonard J. Schulman

Proceedings of the Conference on Learning Theory, 2021

2020

Unique end of potential line.

John Fearnley, Spencer Gordon, Ruta Mehta, Rahul Savani

J. Comput. Syst. Sci., 2020

The Sparse Hausdorff Moment Problem, with Application to Topic Models.

Spencer Gordon, Bijan Mazaheri, Leonard J. Schulman, Yuval Rabani

CoRR, 2020

2018

End of Potential Line.

John Fearnley, Spencer Gordon, Ruta Mehta, Rahul Savani

CoRR, 2018

2017

CLS: New Problems and Completeness.

John Fearnley, Spencer Gordon, Ruta Mehta, Rahul Savani

CoRR, 2017

Extending Parikh's Theorem to Weighted and Probabilistic Context-Free Grammars.

Vijay Bhattiprolu, Spencer Gordon, Mahesh Viswanathan

Proceedings of the Quantitative Evaluation of Systems - 14th International Conference, 2017