We stand with Ukraine

We stand with Ukraine

Colin Sandon

Affiliations:

Massachusetts Institute of Technology (MIT), Department of Mathematics, Cambridge, MA, USA
Princeton University, Department of Mathematics, J, USA

According to our database¹, Colin Sandon authored at least 26 papers between 2013 and 2024.

Collaborative distances:

Dijkstra number² of three.
Erdős number³ of two.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Links

Online presence:

on math.mit.edu
on ieeexplore.ieee.org

On csauthors.net:

Bibliography

2024

The Power of Two Matrices in Spectral Algorithms for Community Recovery.

[BibT_eX]

[DOI]

,

,

Elchanan Mossel

,

IEEE Trans. Inf. Theory, May, 2024

How Far Can Transformers Reason? The Locality Barrier and Inductive Scratchpad.

[BibT_eX]

[DOI]

,

,

,

,

CoRR, 2024

The power of an adversary in Glauber dynamics.

[BibT_eX]

[DOI]

,

,

Elchanan Mossel

,

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

2023

Reed-Muller codes have vanishing bit-error probability below capacity: a simple tighter proof via camellia boosting.

[BibT_eX]

[DOI]

,

CoRR, 2023

A proof that Reed-Muller codes achieve Shannon capacity on symmetric channels.

[BibT_eX]

[DOI]

,

Proceedings of the 64th IEEE Annual Symposium on Foundations of Computer Science, 2023

2022

The Power of Two Matrices in Spectral Algorithms.

[BibT_eX]

[DOI]

,

,

Elchanan Mossel

,

CoRR, 2022

Spectral Algorithms Optimally Recover (Censored) Planted Dense Subgraphs.

[BibT_eX]

[DOI]

,

,

Elchanan Mossel

,

CoRR, 2022

Spectral recovery of binary censored block models.

[BibT_eX]

[DOI]

,

,

Elchanan Mossel

,

Proceedings of the 2022 ACM-SIAM Symposium on Discrete Algorithms, 2022

2021

Spoofing Generalization: When Can't You Trust Proprietary Models?

[BibT_eX]

[DOI]

,

Elchanan Mossel

,

CoRR, 2021

On the Power of Differentiable Learning versus PAC and SQ Learning.

[BibT_eX]

[DOI]

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,

,

,

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

Learning to Sample from Censored Markov Random Fields.

[BibT_eX]

[DOI]

,

Elchanan Mossel

,

Proceedings of the Conference on Learning Theory, 2021

2020

Graph Powering and Spectral Robustness.

[BibT_eX]

[DOI]

,

Enric Boix-Adserà

,

,

SIAM J. Math. Data Sci., 2020

Poly-time universality and limitations of deep learning.

[BibT_eX]

[DOI]

,

CoRR, 2020

On the universality of deep learning.

[BibT_eX]

[DOI]

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Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Parallels Between Phase Transitions and Circuit Complexity?

[BibT_eX]

[DOI]

,

Elchanan Mossel

,

Proceedings of the Conference on Learning Theory, 2020

2019

The Circuit Complexity of Inference.

[BibT_eX]

[DOI]

,

Elchanan Mossel

,

CoRR, 2019

2018

Provable limitations of deep learning.

[BibT_eX]

[DOI]

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CoRR, 2018

2017

Community Detection in the Stochastic Block Model: fundamental limits

[BibT_eX]

[DOI]

PhD thesis, 2017

2016

Linear Boolean Classification, Coding and the Critical Problem.

[BibT_eX]

[DOI]

,

,

Afonso S. Bandeira

,

IEEE Trans. Inf. Theory, 2016

Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation.

[BibT_eX]

[DOI]

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Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Crossing the KS threshold in the stochastic block model with information theory.

[BibT_eX]

[DOI]

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Proceedings of the IEEE International Symposium on Information Theory, 2016

2015

Detection in the stochastic block model with multiple clusters: proof of the achievability conjectures, acyclic BP, and the information-computation gap.

[BibT_eX]

[DOI]

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CoRR, 2015

Community detection in general stochastic block models: fundamental limits and efficient recovery algorithms.

[BibT_eX]

[DOI]

,

CoRR, 2015

Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters.

[BibT_eX]

[DOI]

,

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Community Detection in General Stochastic Block models: Fundamental Limits and Efficient Algorithms for Recovery.

[BibT_eX]

[DOI]

,

Proceedings of the IEEE 56th Annual Symposium on Foundations of Computer Science, 2015

2013

Warnaar's bijection and colored partition identities, I.

[BibT_eX]

[DOI]

,

Fabrizio Zanello

J. Comb. Theory A, 2013

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