Faculty

Institution

Unit

Venue

David Gamarnik

Nanyang Technological University Professor of Operations Research Professor of Operations Research

Massachusetts Institute of Technology

Affiliations

MIT Schwarzman College of Computing

Data, Systems, and Society

David Gamarnik is currently serving as a Data, Systems, And Society Nanyang Technological University Professor of Operations Research Professor of Operations Research at Massachusetts Institute of Technology.

Honors

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Experiences

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Education

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David Gamarnik

Massachusetts Institute of Technology

Nanyang Technological University Professor of Operations Research Professor of Operations Research

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applied mathematics computer science queueing theory graph theory machine learning operations research probability theory mathematical optimization statistics applied probability stability data science stochastic process overlap gap property combinatorics scientific computing information theory estimation theory fluid queue combinatorial optimization discrete algorithms automatic control statistical methodology bayesian inference matrix analysis probabilistic graph theory matrix theory stochastic optimization poisson boundary fluid models sparse random graphs stability conditions engineering optimization combinatorial theory machine learning research operation management statistical physics random graphs learning theory bibliometrics network optimization parameter estimation lower bounds many servers shortest queue whole graph log-partition function local algorithms sequential cavity method adversarial queueing networks correlation decay random optimization problems giant component squared error deterministic approximation algorithm structural optimization telecommunication networks numerical algorithms computational optimization management science probabilistic analysis stochastic systems stochastic networks routing protocols adversarial machine learning network routing scheduling analysis constraint satisfaction matching technique graph matching combinatorial pattern matching stress management workload management congestion management benchmark studies robust optimization

Notable Scholarly Works

Notable Federal Grants

Collaborators

Bounds on the Ground State Energy of Quantum $P$-Spin Hamiltonians. arXiv (Cornell University) (2024)

Anschuetz, Eric R.Gamarnik, DavidKiani, Bobak T.

physicsparticle physicsground state energy

Circuit Lower Bounds for the P-Spin Optimization Problem. Markov Processes And Related Fields (2024)

D. GamarnikA. JagannathA.S. Wein

engineering optimizationcontrol systemsp-spin optimization problemoptimization problemscircuit lower boundspower electronicselectrical engineering

Combinatorial Nlts From the Overlap Gap Property. Quantum (2024)

Eric R. AnschuetzDavid GamarnikBobak Kiani

combinatorial nltscombinatoricsoverlap gap property

Hardness of Random Optimization Problems for Boolean Circuits, Low-Degree Polynomials, and Langevin Dynamics. SIAM Journal on Computing (2024)

David GamarnikAukosh JagannathAlexander S. Wein

boolean circuitslow-degree polynomialslangevin dynamicsrandom optimization problemscomputer science

Stationary Points of a Shallow Neural Network With Quadratic Activations and the Global Optimality of the Gradient Descent Algorithm. Mathematics of Operations Research (2024)

David GamarnikEren C. KızıldağIlias Zadik

stationary pointsgradient descent algorithmquadratic activationsglobal optimizationshallow neural networkapplied mathematicsmachine learningglobal optimalityoperations research

The Landscape of the Planted Clique Problem: Dense Subgraphs and the Overlap Gap Property. The Annals of Applied Probability (2024)

David GamarnikIlias Zadik

planted clique problemdense subgraphsgraph theoryoverlap gap propertyapplied mathematics

Algorithmic Obstructions in the Random Number Partitioning Problem. The Annals of Applied Probability (2023)

David GamarnikEren C. Kızıldağ

applied probabilityalgorithmic obstructionsprobability theoryapplied mathematics

Barriers for the Performance of Graph Neural Networks (Gnn) in Discrete Random Structures. Proceedings of the National Academy of Sciences (2023)

David Gamarnik

graph theorycomputer sciencediscrete random structuresgraph neural networks

Geometric Barriers for Stable and Online Algorithms for Discrepancy Minimization. arXiv (Cornell University) (2023)

Gamarnik, DavidKızıldağ, Eren C.Perkins, WillXu, Changji

geometric barriersmachine learningdiscrepancy minimizationapplied mathematics

Product States Optimize Quantum $P$-Spin Models for Large $P$. arXiv (Cornell University) (2023)

Anschuetz, Eric R.Gamarnik, DavidKiani, Bobak T.

product statesparticle physicsapplied mathematics

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David Gamarnik

Nanyang Technological University Professor of Operations Research Professor of Operations Research

Massachusetts Institute of Technology

Affiliations

MIT Schwarzman College of Computing

Data, Systems, and Society

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

David Gamarnik

Massachusetts Institute of Technology

Nanyang Technological University Professor of Operations Research Professor of Operations Research

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Bounds on the Ground State Energy of Quantum $P$-Spin Hamiltonians. arXiv (Cornell University) (2024)

Anschuetz, Eric R.Gamarnik, DavidKiani, Bobak T.

physicsparticle physicsground state energy

Circuit Lower Bounds for the P-Spin Optimization Problem. Markov Processes And Related Fields (2024)

D. GamarnikA. JagannathA.S. Wein

engineering optimizationcontrol systemsp-spin optimization problemoptimization problemscircuit lower boundspower electronicselectrical engineering

Combinatorial Nlts From the Overlap Gap Property. Quantum (2024)

Eric R. AnschuetzDavid GamarnikBobak Kiani

combinatorial nltscombinatoricsoverlap gap property

Hardness of Random Optimization Problems for Boolean Circuits, Low-Degree Polynomials, and Langevin Dynamics. SIAM Journal on Computing (2024)

David GamarnikAukosh JagannathAlexander S. Wein

boolean circuitslow-degree polynomialslangevin dynamicsrandom optimization problemscomputer science

Stationary Points of a Shallow Neural Network With Quadratic Activations and the Global Optimality of the Gradient Descent Algorithm. Mathematics of Operations Research (2024)

David GamarnikEren C. KızıldağIlias Zadik

stationary pointsgradient descent algorithmquadratic activationsglobal optimizationshallow neural networkapplied mathematicsmachine learningglobal optimalityoperations research

The Landscape of the Planted Clique Problem: Dense Subgraphs and the Overlap Gap Property. The Annals of Applied Probability (2024)

David GamarnikIlias Zadik

planted clique problemdense subgraphsgraph theoryoverlap gap propertyapplied mathematics

Algorithmic Obstructions in the Random Number Partitioning Problem. The Annals of Applied Probability (2023)

David GamarnikEren C. Kızıldağ

applied probabilityalgorithmic obstructionsprobability theoryapplied mathematics

Barriers for the Performance of Graph Neural Networks (Gnn) in Discrete Random Structures. Proceedings of the National Academy of Sciences (2023)

David Gamarnik

graph theorycomputer sciencediscrete random structuresgraph neural networks

Geometric Barriers for Stable and Online Algorithms for Discrepancy Minimization. arXiv (Cornell University) (2023)

Gamarnik, DavidKızıldağ, Eren C.Perkins, WillXu, Changji

geometric barriersmachine learningdiscrepancy minimizationapplied mathematics

Product States Optimize Quantum $P$-Spin Models for Large $P$. arXiv (Cornell University) (2023)

Anschuetz, Eric R.Gamarnik, DavidKiani, Bobak T.

product statesparticle physicsapplied mathematics

1
2
3
4
5
13
10 / page

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engineering systems

complex system

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graph theory

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data-driven decision support

Sheldon Mark Ross

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wireless communication

Chen Chen

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technological forecasting

quantitative management

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