Making the seminar pages a little more compact with an 'expand' abstract
button.pull/1/head
parent
ed9bf75bd0
commit
5fc818947a
4
Makefile
4
Makefile
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@ -23,5 +23,7 @@ push: fetch all
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find . -name .DS_Store | xargs rm
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rsync -avz -e ssh --safe-links --progress site/ gram:/var/www/static/
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open: all
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open site/index.html
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.PHONY: all fetch push
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.PHONY: all fetch push open
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@ -1,13 +1,16 @@
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.seminar .event {
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margin-top: 20px;
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margin-bottom: 50px;
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padding-top: 20px;
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margin-top: 10px;
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margin-bottom: 20px;
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border-top: 1px solid gray;
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}
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.seminar .event .left_details {
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display: inline-block;
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width: 220px;
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vertical-align: top;
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padding-left: 10px;
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}
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.seminar .event .right_details {
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display: inline-block;
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@ -32,11 +35,12 @@
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.seminar .event .details_body {
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float: clear;
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font-size: 16px;
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font-size: 14px;
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text-align: justify;
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width: 500px;
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width: 550px;
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margin-left: auto;
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margin-right: auto;
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line-height: 18px;
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}
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.seminar .event .details_body a.paper {
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margin-top: 10px;
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@ -49,3 +53,20 @@
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text-align: center;
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font-size: 18px;
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text-decoration: underline;
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}
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.seminar .details_expand {
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margin-left: auto;
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margin-right: auto;
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width: 200px;
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text-align: center;
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margin-bottom: 0px;
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padding-bottom: 0px;
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}
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.seminar .hidden {
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visibility: hidden;
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height: 0px;
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margin-top: 0px;
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margin-bottom: 0px;
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}
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@ -4,24 +4,26 @@ schedule:
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- when: Jan. 25
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what: Brainstorming Joint Project Ideas
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who: The UB Database Group
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where: Davis 113A
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- when: Feb. 1
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what: TBD
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- when: Feb. 8
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what: Reenacting Transactional Histories to Compute Their Provenance
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who: Boris Glavic (IIT)
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where: Location TBD
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abstract: |
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Provenance for database queries, information about how the outputs of a query where derived from its inputs, has recently gained traction in the database community resulting in the development of several models and their implementation in prototype systems. However, currently there is no system or model that supports transactional updates limiting the applicability of provenance to databases which are never updated. In this talk, I introduce reenactment, a novel declarative replay technique for transactional histories, and demonstrate how reenactment can be used to retroactively compute the provenance of past updates, transactions, and histories. The foundation of this research are MV-semirings, our extension of the well-established semiring provenance model for queries to updates and transactions running under multi-versioning concurrency control protocols. In this model, any transactional history (or part thereof) can be simulated through a query, i.e., any state of a relation R produced by a history can be reconstructed by a query. We call this process reenactment. More formally, the reenactment query for a transactional history H is equivalent (in the sense of query equivalence) to the history under MV-semiring semantics. These formal underpinnings are the basis of an efficient approach for computing provenance of past transactions using a standard relational DBMS. I will show how reenactment queries can be constructed from an audit log, a log of past SQL operations, and how queries with MV-semiring semantics can be encoded as standard relational queries. A naive implementation would either require replay of the complete history from the beginning or proactive materialization of provenance while transactions are run. However, as long as a transaction time history is available, reenactment can be started from any past history state. Since most modern DBMS support audit logs and time travel (querying transaction time histories) out of the box and these features incur only moderate overhead on transaction execution, this approach enables efficient provenance computation for transactions on-top of standard database systems. I present encouraging experimental results based on our implementation of these techniques in our GProM (Generic Provenance Middleware) provenance database middleware.
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bio: |
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Boris Glavic is an Assistant Professor of Computer Science at the Illinois Institute of Technology where he leads the IIT database group (<a href="http://www.cs.iit.edu/%7Edbgroup/">http://www.cs.iit.edu/~dbgroup/</a>). Before coming to IIT, Boris spent to two years as a PostDoc in the <a href="http://www.cs.toronto.edu/">Department of Computer Science</a> at the <a href="http://www.utoronto.ca/">University of Toronto</a> working at the <a href="http://dblab.cs.toronto.edu/home/">Database Research Group</a> under <a href="http://www.cs.toronto.edu/%7Emiller">Renée J. Miller</a>. He received a Diploma (Master) in Computer Science from the <a href="http://www.informatik.rwth-aachen.de/">RWTH Aachen</a> in Germany, and a PhD in Computer Science from the University of Zurich in Switzerland being advised by <a href="http://www.ifi.uzh.ch/dbtg/Staff/Boehlen">Michael Böhlen</a> and <a href="http://people.inf.ethz.ch/alonso/">Gustavo Alonso</a>. Boris is a professed database guy enjoying systems research based on solid theoretical foundations. His main research interests are provenance and information integration. He has build several provenance-aware systems (see <a href="http://cs.iit.edu/%7Edbgroup/research/index.html">http://cs.iit.edu/~dbgroup/research/index.html</a>) including Perm (relational databases), Ariadne (stream processing), GProM (database provenance middleware), Vagabond, and LDV (database virtualization and repeatability).
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where: Davis 113A
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details:
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abstract: |
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Provenance for database queries, information about how the outputs of a query where derived from its inputs, has recently gained traction in the database community resulting in the development of several models and their implementation in prototype systems. However, currently there is no system or model that supports transactional updates limiting the applicability of provenance to databases which are never updated. In this talk, I introduce reenactment, a novel declarative replay technique for transactional histories, and demonstrate how reenactment can be used to retroactively compute the provenance of past updates, transactions, and histories. The foundation of this research are MV-semirings, our extension of the well-established semiring provenance model for queries to updates and transactions running under multi-versioning concurrency control protocols. In this model, any transactional history (or part thereof) can be simulated through a query, i.e., any state of a relation R produced by a history can be reconstructed by a query. We call this process reenactment. More formally, the reenactment query for a transactional history H is equivalent (in the sense of query equivalence) to the history under MV-semiring semantics. These formal underpinnings are the basis of an efficient approach for computing provenance of past transactions using a standard relational DBMS. I will show how reenactment queries can be constructed from an audit log, a log of past SQL operations, and how queries with MV-semiring semantics can be encoded as standard relational queries. A naive implementation would either require replay of the complete history from the beginning or proactive materialization of provenance while transactions are run. However, as long as a transaction time history is available, reenactment can be started from any past history state. Since most modern DBMS support audit logs and time travel (querying transaction time histories) out of the box and these features incur only moderate overhead on transaction execution, this approach enables efficient provenance computation for transactions on-top of standard database systems. I present encouraging experimental results based on our implementation of these techniques in our GProM (Generic Provenance Middleware) provenance database middleware.
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bio: |
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Boris Glavic is an Assistant Professor of Computer Science at the Illinois Institute of Technology where he leads the IIT database group (<a href="http://www.cs.iit.edu/%7Edbgroup/">http://www.cs.iit.edu/~dbgroup/</a>). Before coming to IIT, Boris spent to two years as a PostDoc in the <a href="http://www.cs.toronto.edu/">Department of Computer Science</a> at the <a href="http://www.utoronto.ca/">University of Toronto</a> working at the <a href="http://dblab.cs.toronto.edu/home/">Database Research Group</a> under <a href="http://www.cs.toronto.edu/%7Emiller">Renée J. Miller</a>. He received a Diploma (Master) in Computer Science from the <a href="http://www.informatik.rwth-aachen.de/">RWTH Aachen</a> in Germany, and a PhD in Computer Science from the University of Zurich in Switzerland being advised by <a href="http://www.ifi.uzh.ch/dbtg/Staff/Boehlen">Michael Böhlen</a> and <a href="http://people.inf.ethz.ch/alonso/">Gustavo Alonso</a>. Boris is a professed database guy enjoying systems research based on solid theoretical foundations. His main research interests are provenance and information integration. He has build several provenance-aware systems (see <a href="http://cs.iit.edu/%7Edbgroup/research/index.html">http://cs.iit.edu/~dbgroup/research/index.html</a>) including Perm (relational databases), Ariadne (stream processing), GProM (database provenance middleware), Vagabond, and LDV (database virtualization and repeatability).
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- when: Feb. 15
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who: Zack Ives (UPenn)
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what: Title TBD
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where: Location TBD
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where: Davis 113A
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- when: Feb. 22
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what: Mining and Understanding Software Enclaves
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who: Chris Jermaine (Rice University)
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where: Location TBD
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where: Davis 113A
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- when: Feb. 29
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what: TBD
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- when: Mar. 7
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@ -31,14 +33,15 @@ schedule:
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- when: Mar. 21
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who: Wolfgang Gatterbauer (CMU)
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what: Approximate lifted inference with probabilistic databases
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abstract: |
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Probabilistic inference over large data sets is becoming a central data management problem. Recent large knowledge bases, such as Yago, Nell or DeepDive have millions to billions of uncertain tuples. Yet probabilistic inference is known to be #P-hard in the size of the database, even for some very simple queries. This talk shows a new approach that allows ranking answers to hard probabilistic queries in guaranteed polynomial time, and by using only basic operators of existing database management systems (e.g., no sampling required).<br/>
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(1) The first part of this talk develops upper and lower bounds for the probability of Boolean functions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. We call this approach dissociation and give an exact characterization of optimal oblivious bounds, i.e. when the new probabilities are chosen independent of the probabilities of all other variables. Our new bounds shed light on the connection between previous relaxation-based and model-based approximations and unify them as concrete choices in a larger design space.<br/>
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(2) The second part then draws the connection to lifted inference and shows how application of this theory allows a standard relational database management system to both upper and lower bound hard probabilistic queries in guaranteed polynomial time. We give experimental evidence on synthetic TPC-H data that our approach is by orders of magnitude faster and also more accurate than currently used sampling-based approaches.<br/>
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(Talk based on joint work with Dan Suciu from TODS 2014 and VLDB 2015: http://arxiv.org/abs/1409.6052, http://arxiv.org/pdf/1412.1069)
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bio: |
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Wolfgang Gatterbauer is an Assistant Professor in Business Technologies and Computer Science at CMU. His current research focus is on scalable approaches to perform inference over uncertain data. He received degrees in Mechanical Engineering, Electrical Engineering & Computer Science, and Technology & Policy, and then got his PhD in Computer Science from Vienna University of Technolgoy. Prior to joining CMU, he was a Post-Doc in the Database group at University of Washington. In earlier times, he won a Bronze medal at the International Physics Olympiad, worked in the steam turbine development department of ABB Alstom Power, and in the German office of McKinsey & Company.
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where: Location TBD
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where: Davis 113A
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details:
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abstract: |
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Probabilistic inference over large data sets is becoming a central data management problem. Recent large knowledge bases, such as Yago, Nell or DeepDive have millions to billions of uncertain tuples. Yet probabilistic inference is known to be #P-hard in the size of the database, even for some very simple queries. This talk shows a new approach that allows ranking answers to hard probabilistic queries in guaranteed polynomial time, and by using only basic operators of existing database management systems (e.g., no sampling required).<br/>
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(1) The first part of this talk develops upper and lower bounds for the probability of Boolean functions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. We call this approach dissociation and give an exact characterization of optimal oblivious bounds, i.e. when the new probabilities are chosen independent of the probabilities of all other variables. Our new bounds shed light on the connection between previous relaxation-based and model-based approximations and unify them as concrete choices in a larger design space.<br/>
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(2) The second part then draws the connection to lifted inference and shows how application of this theory allows a standard relational database management system to both upper and lower bound hard probabilistic queries in guaranteed polynomial time. We give experimental evidence on synthetic TPC-H data that our approach is by orders of magnitude faster and also more accurate than currently used sampling-based approaches.<br/>
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(Talk based on joint work with Dan Suciu from TODS 2014 and VLDB 2015: http://arxiv.org/abs/1409.6052, http://arxiv.org/pdf/1412.1069)
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bio: |
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Wolfgang Gatterbauer is an Assistant Professor in Business Technologies and Computer Science at CMU. His current research focus is on scalable approaches to perform inference over uncertain data. He received degrees in Mechanical Engineering, Electrical Engineering & Computer Science, and Technology & Policy, and then got his PhD in Computer Science from Vienna University of Technolgoy. Prior to joining CMU, he was a Post-Doc in the Database group at University of Washington. In earlier times, he won a Bronze medal at the International Physics Olympiad, worked in the steam turbine development department of ABB Alstom Power, and in the German office of McKinsey & Company.
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- when: Mar. 28
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what: TBD
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- when: Apr. 4
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@ -69,7 +72,6 @@ The UBDB seminar meets on Mondays at 10:30 AM, typically in Davis 113A. Subscri
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<div class="seminar">
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{{#each schedule}}
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<div class="event">
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<div class="left_details">
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<div class="date">{{when}}</div>
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@ -79,18 +81,22 @@ The UBDB seminar meets on Mondays at 10:30 AM, typically in Davis 113A. Subscri
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<div class="title">{{what}}</div>
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{{#if who}}<div class="speaker">{{who}}</div>{{/if}}
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</div>
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<div class="details_body">
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{{#if url}}<center><a href="{{url}}" class="paper">{{url}}</a></center>{{/if}}
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{{#if abstract}}
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{{#if url}}<center><a href="{{url}}" class="paper">{{url}}</a></center>{{/if}}
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{{#if details}}
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<div class="details_expand" id="Expand {{when}}">
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<a href="#" onclick="document.getElementById('Expand {{when}}').className += ' hidden'; document.getElementById('Details {{when}}').className = 'details_body'; return false;">-- show details --</a>
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</div>
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<div class="details_body hidden" id="Details {{when}}">
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{{#if details/abstract}}
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<div class="heading">Abstract</div>
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{{{abstract}}}
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{{{details/abstract}}}
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{{/if}}
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{{#if bio}}
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{{#if details/bio}}
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<div class="heading">Bio</div>
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{{{bio}}}
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{{{details/bio}}}
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{{/if}}
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</div>
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{{/if}}
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</div>
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{{/each}}
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</div>
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