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9 papers
A Fast Quantitative Analyzer for NetKAT
Thomas Lu, Qiancheng Fu, Kevin Batz +5
When designing a network, engineers must navigate trade-offs (e.g., one topology offers more aggregate bandwidth, another lower latency or better resilience) that demand reasoning…
Active Learning of Symbolic NetKAT Automata
Mark Moeller, Tiago Ferreira, Thomas Lu +2
NetKAT is a domain-specific programming language and logic that has been successfully used to specify and verify the behavior of packet-switched networks. This paper develops techn…
Unboxing Virgil ADTs for Fun and Profit
Bradley Wei Jie Teo, Ben L. Titzer
Algebraic Data Types (ADTs) are an increasingly common feature in modern programming languages. In many implementations, values of non-nullary, multi-case ADTs are allocated on the…
Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov Model
Ding Zhou, Yuanjun Gao, Liam Paninski
The Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) has been used widely as a natural Bayesian nonparametric extension of the classical Hidden Markov Model for learnin…
Proceedings ML Family Workshop / OCaml Users and Developers workshops
Kenichi Asai, Mark Shinwell
This volume contains the joint post-proceedings of the 2016 edition of the ML Family Workshop and OCaml Users and Developers Workshop, held in Nara, Japan, in affiliation with ICFP…
Algebraic Geometry of Matrix Product States
Andrew Critch, Jason Morton
We quantify the representational power of matrix product states (MPS) for entangled qubit systems by giving polynomial expressions in a pure quantum state's amplitudes which hold i…