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Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting
Hamiltonian Monte Carlo (HMC) is a Markov chain Monte Carlo (MCMC) approach that exhibits favourable exploration properties in …
Adam D. Cobb, Brian Jalaian
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Fountain Coding for Information Protection in Tactical Networks
Tactical edge networks are operated in harsh conditions where ensuring information protection is a challenging issue. An insider threat …
Vignesh Sridharan, Mehul Motani, Brian Jalaian, Niranjan Suri
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Machine learning raw network traffic detection
Increasingly cyber-attacks are sophisticated and occur rapidly, necessitating the use of machine learning techniques for detection at …
Michael J. De Lucia, Paul E. Maxwell, Nathaniel D. Bastian, Ananthram Swami, Brian Jalaian, Nandi Leslie
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Better call Surrogates: A hybrid Evolutionary Algorithm for Hyperparameter optimization
In this paper, we propose a surrogate-assisted evolutionary algorithm (EA) for hyperparameter optimization of machine learning (ML) …
Subhodip Biswas, Adam D Cobb, Andreea Sistrunk, Naren Ramakrishnan, Brian Jalaian
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On Uncertainty and Robustness in Large-Scale Intelligent Data Fusion Systems
The resurgence of AI in the recent decade dramatically changes the design of modern sensor data fusion systems, leading to new …
Benjamin M. Marlin, Tarek Abdelzaher, Gabriela Ciocarlie, Adam D. Cobb, Mark Dennison, Brian Jalaian, Lance Kaplan, Tiffany Raber, Adrienne Raglin, Piyush K. Sharma, Mani Srivastava, Theron Trout, Meet P. Vadera, Maggie Wigness
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URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks
While deep learning methods continue to improve in predictive accuracy on a wide range of application domains, significant issues …
Meet P. Vadera, Adam D. Cobb, Brian Jalaian, Benjamin M. Marlin
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Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks
In this paper, we present a general framework for distilling expectations with respect to the Bayesian posterior distribution of a deep …
Meet P. Vadera, Brian Jalaian, Benjamin M. Marlin
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A Real-Time Solution for Underlay Coexistence with Channel Uncertainty
Underlay coexistence is an effective mechanism to improve spectrum effïciency by having picocells coexist with macrocell on the same …
S Li, Y Huang, C Li, B Jalaian, S Russell, Y T Hou, W Lou, B MacCall
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Optimal Power Control with Channel Uncertainty in Ad Hoc Networks
We consider a practical ad hoc network where the channel gains from the transmitters to the receivers are only known through their mean …
S Li, Y T Hou, W Lou, B Jalaian, S Russell, B MacCall
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Attribution-driven causal analysis for detection of adversarial examples
Attribution methods have been developed to explain the decision of a machine learning model on a given input. We use the Integrated …
Susmit Jha, Sunny Raj, Steven Lawrence Fernandes, Sumit Kumar Jha, Somesh Jha, Gunjan Verma, Brian Jalaian, Ananthram Swami
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