2018 Fall
Welcome to the homepage of CSE 645 (Fall 2018) Seminar in Languages!
General Information
Course description: We will read papers and discuss research ranging from high-level specifications (such as logic, rules, and sets) to algorithms and methods for efficient implementations, with a wide range of applications.
For this semester, we will include the following four topics and possibly others: probabilistic programming, quantum computing, knowledge base languages, and languages for security.
In particular, we will start each topic from scratch, and discuss the best overview and survey papers that lead to the state of the art.
Everyone is welcome. If you are enrolled in the class, you are expected to attend a majority of the meetings and present a paper.
Instructors: Annie Liu, CR Ramakrishnan, Michael Kifer, David Warren, and Paul Fodor (contact: paul.fodor@stonybrook.edu).
Hours: Thursdays, 11:30AM-12:50PM, in New Computer Science, Room 220.
Previous semesters: Spring 2018,
Fall 2015, Spring 2015, Fall 2014, Spring 2014, Fall 2013, Spring 2013, Fall 2012, Spring 2012, Fall 2011, Spring 2011, Fall 2010, Spring 2010, Fall 2009, Spring 2009, Fall 2008 ,earlier semesters
.
Schedule
8/30 Organizational meeting.
9/6 Prof. Tzu-Chieh Wei, physics, will give an introductory talk on Quantum Computing.
9/13 Prof. CR Ramakrishnan gave an introduction to Probabilistic Logic Programming, and we will watch Stuart Russell: Unifying logic & probability: the BLOG language: https://www.youtube.com/watch?v=LN1ubjPdb_c
9/20 We experimented with BLOG. Lead by Prof. CR Ramakrishnan.
Example: https://sites.google.com/site/bloginference/example-usage/burglary-earthquake-network
Blog Web site: https://bayesianlogic.github.io/
Slides: https://bayesianlogic.github.io/download/BLOG-tutorial-2014.pdf
9/27 Annie Liu presented Founded Semantics
Christopher Kane will lead the discussion on High-Level Cryptographic Abstraction (to be rescheduled)
10/4 Michael Kifer's talk on Elements of Rule-based Knowledge Representation and Reasoning (https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnxzYmNzbGFuZ3VhZ2VzZW1pbmFyfGd4OjVkNmZhODA4ZWNhZDgxMmM)
10/11 Michael Kifer finished his talk about Elements of Rule-based Knowledge Representation and Reasoning
Luming Wu started the discussion on Fixpoint Semantics and Optimization of Recursive Datalog Programs with Aggregates, Carlo Zaniolo, Mohan Yang, Matteo Interlandi, Ariyam Das, Alexander Shkapsky, Tyson Condie. ICLP2017.
https://arxiv.org/pdf/1707.05681.pdf
10/18 Matthew Weston will lead the discussion on Declaratively solving tricky Google Code Jam problems with Prolog-based ECLiPSe CLP system,Sergii Dymchenko && Mariia Mykhailova, 2014.
https://arxiv.org/pdf/1412.2304.pdf
10/25 James Morris will lead the discussion on Probabilistic Logic Models and Their Application to Breast Cancer, Joana Corte-Real, Ines Dutra, and Ricardo Rocha , Inductive Logic Programming Conference,2017.
https://ilp2017.sciencesconf.org/data/pages/ILP_2017_paper_33.pdf
Thesis: http://www.dcc.fc.up.pt/~ricroc/homepage/alumni/2018-corterealPhD.pdf
FOIL: https://en.wikipedia.org/wiki/First-order_inductive_learner
James' presentation: https://docs.google.com/presentation/d/1jQqJI6FdjQz9A3q8LkAbzfwhGDrnXj1aMpba7T5SC-o/edit?usp=sharing
11/1 James will continue his presentation.
11/8 Shanshan Chen will lead the discussion on Estimating Accuracy from Unlabeled Data A Probabilistic Logic Approach,Emmanouil A. Platanios, Hoifung Poon, Tom M. Mitchell,Eric Horvitz, NIPS 2017.
https://arxiv.org/pdf/1705.07086.pdf
Rushil Sharma will lead the discussion on A logical approach to working with biological databases , Nicos Angelopoulos and Georgios Giamas, ICLP 2015
http://ceur-ws.org/Vol-1433/tc_74.pdf
11/15 Caitao Zhan will lead the discussion on Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge, Luciano Serafini and Artur d’Avila Garcez, 2016.
https://arxiv.org/pdf/1606.04422.pdf
Sarthak Ghosh will help with the presentation.
11/22 Thanksgiving
11/29 Tianchi (Maverick) Mo will lead the discussion on Improving Adherence to Heart Failure Management Guidelines via Abductive Reasoning,Zhuo Chen, Elmer Salazar, Kyle Marple, Gopal Gupta, Lakshman Tamil, ICLP 2017.
12/6 Jason Irukulapati will lead the discussion on Lifted Variable Elimination For Probabilistic Logic Programming,Elena Bellodi , Evelina Lamma , Fabrizio Riguzzi Vitor Santos Costa , Riccardo Zese. TPLP, 2014
https://arxiv.org/pdf/1405.3218.pdf
Delay to next semester:
Bladimil Nunez will lead the discussion on Lock-free atom garbage collection for multithreaded Prolog Jan Wielemaker, Keri Harris, ICLP, 2016
Jamshed Khan will lead the discussion on Solving Probability Problems in Natural Language. Anton Dries, Angelika Kimmig, Jesse Davis, Vaishak Belle, Luc De Raedt. IJCAI 2017: 3981-3987.https://www.ijcai.org/proceedings/2017/0556.pdf
Mingchen Zhang will lead the discussion on Open-World Probabilistic Databases,Ismail Ilkan Ceylan and Adnan Darwiche and Guy Van den Broeck, KR 2016.
https://web.cs.ucla.edu/~guyvdb/papers/CeylanKR16.pdf
Papers
Below are some possible papers from before, and more paper will be available.
Logic and Databases related papers: https://simons.berkeley.edu/talks/logic-and-databases
Fixpoint Semantics and Optimization of Recursive Datalog Programs with Aggregates. Carlo Zaniolo, Mohan Yang, Matteo Interlandi, Ariyam Das, Alexander Shkapsky, Tyson Condie. ICLP2017.
https://arxiv.org/pdf/1707.05681.pdf
A New Algorithm To Automate Inductive Learning Of Default Theories,Farhad Shakerin, Elmer Salazar, Gopal Gupta. ICLP 2017.
Improving Adherence to Heart Failure Management Guidelines via Abductive Reasoning,Zhuo Chen, Elmer Salazar, Kyle Marple, Gopal Gupta, Lakshman Tamil, ICLP 2017.
https://arxiv.org/pdf/1707.04957.pdf
Modeling Machine Learning and Data Mining Problems with FO(·),Blockeel, Hendrik, Bogaerts, Bart, Bruynooghe, Maurice, De Cat, Broes, De Pooter, Stef, Denecker, Marc, Labarre, Anthony, Ramon, Jan, Verwer, Sicco,Technical Communications of ICLP 2012.
https://hal.archives-ouvertes.fr/hal-00731459/document
Learning constraints in spreadsheets and tabular data. Samuel Kolb, Sergey Paramonov, Tias Guns, Luc De Raedt. Machine Learning 106(9-10): 1441-1468 (2017)
Solving Probability Problems in Natural Language. Anton Dries, Angelika Kimmig, Jesse Davis, Vaishak Belle, Luc De Raedt. IJCAI 2017: 3981-3987
https://www.ijcai.org/proceedings/2017/0556.pdf
Probabilistic Logic Models and Their Application to Breast Cancer,Joana Corte-Real, Ines Dutra, and Ricardo Rocha ,Inductive Logic Programming Conference,2017.
DeepMath - Deep Sequence Models for Premise Selection,Alexander A. Alemi, François Chollet, Niklas Een, Geoffrey Irving, Christian Szegedy, Josef Urban,Computing Research Repository (CoRR) - cs.AI,2016
Clingo goes Linear Constraints over Reals and Integers,Tomi Janhunen, Roland Kaminski, Max Ostrowski, Torsten Schaub, Sebastian Schellhorn, Philipp Wanko,ICLP,2017
Plan Failure Analysis and Interactive Planning Through Natural Language Communication,Chitta Baral and Tran Cao Son,LPNMR,2015
Declaratively solving tricky Google Code Jam problems with Prolog-based ECLiPSe CLP system,Sergii Dymchenko && Mariia Mykhailova,,2014
Shift Design with Answer Set Programming,Michael Abseher, Martin Gebser, Nysret Musliu, Torsten Schaub and Stefan Woltran,Eighth ASPOCP International Workshop on “Answer Set Programming and Other Computing Paradigms”,17 November 2016
Searching Personnel Relationship from Myanmar Census Data using Graph Database and Deductive Reasoning Prolog Rules,Kay Thi Yar, Khin Mar Lar Tun ,2016 International Conference on Computer Communication and Informatics,2016
Lifted Variable Elimination For Probabilistic Logic Programming,Elena Bellodi , Evelina Lamma , Fabrizio Riguzzi Vitor Santos Costa , Riccardo Zese,Tplp,2014
A logical approach to working with biological databases , Nicos Angelopoulos and Georgios Giamas, ICLP 2015, 2015
CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied to Dialog with a Mobile Robot, Shiqi Zhang and Peter Stone, Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015.
Meta-Interpretive Learning: Achievements and Challenges,Stephen H. Muggleton,International Joint Conference, RuleML+RR 2017,2017
Predicate Logic As A Modeling Language: Modeling And Solving Some Machine Learning And Data Mining Problems With Idp3,Maurice Bruynooghe, Hendrik Blockeel, Bart Bogaerts, Broes De Cat, Stef De Pooter, Joachim Jansen, Anthony Labarre, Jan Ramon, Marc Denecker,Idp,2014
Logical Vision: Meta-Interpretive Learning for Simple Geometrical Concepts, Wang-Zhou Dai, Stephen H. Muggleton, Zhi-Hua Zhou, Inductive Logic Programming (ILP), 2015
Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge, Luciano Serafini and Artur d’Avila Garcez, 2016
Semantic code browsing, Isabel Garci ´A-Contreras1, Jose ´ F. Morales1 And Manuel V. Hermenegildo, ICLP 2016, 2016
Lock-free atom garbage collection for multithreaded Prolog, Jan Wielemaker, Keri Harris, ICLP, 2016
Estimating Accuracy from Unlabeled Data A Probabilistic Logic Approach,Emmanouil A. Platanios, Hoifung Poon, Tom M. Mitchell,Eric Horvitz,Nips,2017
Solving Distributed Constraint Optimization Problems Using Logic Programming,Tiep Le, Tran Cao Son, Enrico Pontelli, William Yeoh,ICLP,2017
Open-World Probabilistic Databases,Ismail Ilkan Ceylan and Adnan Darwiche and Guy Van den Broeck,kr2016,2016
Learning Knowledge Base Inference with Neural Theorem Provers,Tim Rocktaschel and Sebastian Riedel,NAACL Workshop on Automated Knowledge Base Construction (AKBC).,2016
Reasoning About Entailment with Neural Attention,Tim Rockt¨aschel , Edward Grefenstette, Karl Moritz, Hermannil Blunsom,ICLR,2016
An ASP application in integrative biology: identification of functional gene units,Philippe Bordron, Damien Eveillard, Alejandro Maass, Anne Siegel, and Sven Thiele,International Conference on Logic Programming and Non-monotonic Reasoning,2013