Christopher J. Quinn

Orcid: 0000-0002-9053-1504

According to our database1, Christopher J. Quinn authored at least 39 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Learning Coupled Subspaces for Multi-Condition Spike Data.
CoRR, 2024

Federated Neural Nonparametric Point Processes.
CoRR, 2024

Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Unsupervised Change Point Detection in Multivariate Time Series.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Combinatorial Stochastic-Greedy Bandit.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
A Community-Aware Framework for Social Influence Maximization.
IEEE Trans. Emerg. Top. Comput. Intell., August, 2023

Size-constrained k-submodular maximization in near-linear time.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

A Unified Approach for Maximizing Continuous DR-submodular Functions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback.
Proceedings of the International Conference on Machine Learning, 2023

Fractional Budget Allocation for Influence Maximization.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
An explore-then-commit algorithm for submodular maximization under full-bandit feedback.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021
Stochastic Top <i>K</i>-Subset Bandits with Linear Space and Non-Linear Feedback with Applications to Social Influence Maximization.
Trans. Data Sci., 2021

Information Flow in Markov Chains.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Stochastic Top-K Subset Bandits with Linear Space and Non-Linear Feedback.
Proceedings of the Algorithmic Learning Theory, 2021

DART: Adaptive Accept Reject Algorithm for Non-Linear Combinatorial Bandits.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
DART: aDaptive Accept RejecT for non-linear top-K subset identification.
CoRR, 2020

Synergy and Redundancy Duality Between Gaussian Multiple Access and Broadcast Channels.
Proceedings of the International Symposium on Information Theory and Its Applications, 2020

Modeling Piece-Wise Stationary Time Series.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
A Measure of Synergy, Redundancy, and Unique Information using Information Geometry.
Proceedings of the IEEE International Symposium on Information Theory, 2019

2017
Bounded-Degree Connected Approximations of Stochastic Networks.
IEEE Trans. Mol. Biol. Multi Scale Commun., 2017

2016
Crowdsourcing High Quality Labels with a Tight Budget.
Proceedings of the Ninth ACM International Conference on Web Search and Data Mining, 2016

Sparse approximations of directed information graphs.
Proceedings of the IEEE International Symposium on Information Theory, 2016

On sparse approximations for time-series networks.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2015
Directed Information Graphs.
IEEE Trans. Inf. Theory, 2015

Bounded Degree Approximations of Stochastic Networks.
CoRR, 2015

2014
Identification and approximation of the structure of networks of stochastic processes
PhD thesis, 2014

Dynamic and Succinct Statistical Analysis of Neuroscience Data.
Proc. IEEE, 2014

2013
Efficient Methods to Compute Optimal Tree Approximations of Directed Information Graphs.
IEEE Trans. Signal Process., 2013

Fingerprinting With Equiangular Tight Frames.
IEEE Trans. Inf. Theory, 2013

Optimal bounded-degree approximations of joint distributions of networks of stochastic processes.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

Robust directed tree approximations for networks of stochastic processes.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

2011
Estimating the directed information to infer causal relationships in ensemble neural spike train recordings.
J. Comput. Neurosci., 2011

Causal Dependence Tree Approximations of Joint Distributions for Multiple Random Processes
CoRR, 2011

Equivalence between minimal generative model graphs and directed information graphs.
Proceedings of the 2011 IEEE International Symposium on Information Theory Proceedings, 2011

Equiangular tight frame fingerprinting codes.
Proceedings of the IEEE International Conference on Acoustics, 2011

A minimal approach to causal inference on topologies with bounded indegree.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
Approximating discrete probability distributions with causal dependence trees.
Proceedings of the International Symposium on Information Theory and its Applications, 2010


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