Fri 25 Jun 2021 09:15 - 09:20 at PLDI-A - Talks 5A: Machine Learning and Probabilistic Programming
Fri 25 Jun 2021 21:15 - 21:20 at PLDI-A - Talks 5A: Machine Learning and Probabilistic Programming
Fri 25 Jun 2021 21:15 - 21:20 at PLDI-A - Talks 5A: Machine Learning and Probabilistic Programming
The problem of synthesizing specifications of undefined procedures has a broad range of applications, but the usefulness of the generated specifications depends on their quality. In this paper, we propose a technique for finding maximal and non-vacuous specifications. Maximality allows for more choices for implementations of undefined procedures, and non-vacuity ensures that safety assertions are reachable.
To handle programs with complex control flow, our technique discovers not only specifications but also inductive invariants. Our iterative algorithm lazily generalizes non-vacuous specifications in a counterexample-guided loop. The key component of our technique is an effective non-vacuous specification synthesis algorithm. We have implemented the approach in a tool called HornSpec, taking as input systems of constrained Horn clauses. We have experimentally demonstrated the tool's effectiveness, efficiency, and the quality of generated specifications on a range of benchmarks.
Fri 25 JunDisplayed time zone: Eastern Time (US & Canada) change
Fri 25 Jun
Displayed time zone: Eastern Time (US & Canada) change
09:00 - 09:40 | |||
09:00 5mTalk | DeepCuts: A Deep Learning Optimization Framework for Versatile GPU Workloads PLDI Wookeun Jung Seoul National University, Thanh Tuan Dao Seoul National University, Jaejin Lee Seoul National University DOI | ||
09:05 5mTalk | Provable Repair of Deep Neural Networks PLDI Matthew Sotoudeh University of California at Davis, Aditya V. Thakur University of California at Davis DOI Pre-print Media Attached | ||
09:10 5mTalk | DreamCoder: Bootstrapping Inductive Program Synthesis with Wake-Sleep Library Learning PLDI Kevin Ellis Cornell University, Lionel Wong Massachusetts Institute of Technology, Maxwell Nye Massachusetts Institute of Technology, Mathias Sablé-Meyer PSL University; Collège de France; NeuroSpin, Lucas Morales Massachusetts Institute of Technology, Luke Hewitt Massachusetts Institute of Technology, Luc Cary Massachusetts Institute of Technology, Armando Solar-Lezama Massachusetts Institute of Technology, Joshua B. Tenenbaum Massachusetts Institute of Technology DOI | ||
09:15 5mTalk | Specification Synthesis with Constrained Horn Clauses PLDI Sumanth Prabhu TCS Research, Grigory Fedyukovich Florida State University, Kumar Madhukar TCS Research, Deepak D'Souza IISc Bangalore DOI | ||
09:20 5mTalk | Compiling Stan to Generative Probabilistic Languages and Extension to Deep Probabilistic Programming PLDI Guillaume Baudart Inria, Javier Burroni University of Massachusetts Amherst, Martin Hirzel IBM Research, Louis Mandel IBM Research, USA, Avraham Shinnar IBM Research DOI | ||
09:25 5mTalk | Sound Probabilistic Inference via Guide Types PLDI Di Wang Carnegie Mellon University, Jan Hoffmann Carnegie Mellon University, Thomas Reps University of Wisconsin DOI | ||
09:30 5mTalk | SPPL: Probabilistic Programming with Fast Exact Symbolic Inference PLDI Feras Saad Massachusetts Institute of Technology, Martin C. Rinard Massachusetts Institute of Technology, Vikash K. Mansinghka Massachusetts Institute of Technology DOI | ||
09:35 5mTalk | Quantitative Analysis of Assertion Violations in Probabilistic Programs PLDI Jinyi Wang Shanghai Jiao Tong University, Yican Sun Peking University, Hongfei Fu Shanghai Jiao Tong University, Krishnendu Chatterjee IST Austria, Amir Kafshdar Goharshady Hong Kong University of Science and Technology DOI | ||
21:00 - 21:40 | |||
21:00 5mTalk | DeepCuts: A Deep Learning Optimization Framework for Versatile GPU Workloads PLDI Wookeun Jung Seoul National University, Thanh Tuan Dao Seoul National University, Jaejin Lee Seoul National University DOI | ||
21:05 5mTalk | Provable Repair of Deep Neural Networks PLDI Matthew Sotoudeh University of California at Davis, Aditya V. Thakur University of California at Davis DOI Pre-print Media Attached | ||
21:10 5mTalk | DreamCoder: Bootstrapping Inductive Program Synthesis with Wake-Sleep Library Learning PLDI Kevin Ellis Cornell University, Lionel Wong Massachusetts Institute of Technology, Maxwell Nye Massachusetts Institute of Technology, Mathias Sablé-Meyer PSL University; Collège de France; NeuroSpin, Lucas Morales Massachusetts Institute of Technology, Luke Hewitt Massachusetts Institute of Technology, Luc Cary Massachusetts Institute of Technology, Armando Solar-Lezama Massachusetts Institute of Technology, Joshua B. Tenenbaum Massachusetts Institute of Technology DOI | ||
21:15 5mTalk | Specification Synthesis with Constrained Horn Clauses PLDI Sumanth Prabhu TCS Research, Grigory Fedyukovich Florida State University, Kumar Madhukar TCS Research, Deepak D'Souza IISc Bangalore DOI | ||
21:20 5mTalk | Compiling Stan to Generative Probabilistic Languages and Extension to Deep Probabilistic Programming PLDI Guillaume Baudart Inria, Javier Burroni University of Massachusetts Amherst, Martin Hirzel IBM Research, Louis Mandel IBM Research, USA, Avraham Shinnar IBM Research DOI | ||
21:25 5mTalk | Sound Probabilistic Inference via Guide Types PLDI Di Wang Carnegie Mellon University, Jan Hoffmann Carnegie Mellon University, Thomas Reps University of Wisconsin DOI | ||
21:30 5mTalk | SPPL: Probabilistic Programming with Fast Exact Symbolic Inference PLDI Feras Saad Massachusetts Institute of Technology, Martin C. Rinard Massachusetts Institute of Technology, Vikash K. Mansinghka Massachusetts Institute of Technology DOI | ||
21:35 5mTalk | Quantitative Analysis of Assertion Violations in Probabilistic Programs PLDI Jinyi Wang Shanghai Jiao Tong University, Yican Sun Peking University, Hongfei Fu Shanghai Jiao Tong University, Krishnendu Chatterjee IST Austria, Amir Kafshdar Goharshady Hong Kong University of Science and Technology DOI | ||