[Caml-list] GCAI 2017 in Miami - Deadline extension

[Caml-list] GCAI 2017 in Miami - Deadline extension

[Geoff Sutcliffe]

---------- deadline extension due to multiple request --------------

       The 3rd Global Conference on Artificial Intelligence (GCAI 2017)
                        Miami, USA, 18-22 October 2017
                 http://easychair.org/smart-program/GCAI2017/

               *New*: (Abstracts: 14 July,  Papers: 21 July)

The 3rd Global Conference on Artificial Intelligence (GCAI 2017) will be held
in Miami, USA, at the Courtyard Marriott hotel in Coconut Grove, 18-22 October
2017. The conference, which addresses all aspects of artificial intelligence,
is being organized by LRG (http://www.lrg.global) and the University of Miami.
The program chairs are Christoph Benzmueller, Christine Lisetti and Martin
Theobald. The conference chair is Geoff Sutcliffe.


SUBMISSION

Submissions in all areas of artifical intelligence are welcome. Suggested
topics include, but are not limited to:


Foundations
+ Knowledge representation
+ Cognitive modeling
+ Perception
+ Search
+ Reasoning and programming
+ Machine learning
+ Constraints and uncertainty

Architectures
+ Agents and distributed AI
+ Intelligent user interfaces
+ Natural language systems and linguistics
+ Information retrieval
+ Case-based reasoning
+ Affective computing
+ Robotics

Applications
+ Aviation and aerospace
+ Education and tutoring systems
+ Games and entertainment
+ Law and Machine Ethics
+ Mathematics and the Sciences
+ Medicine and healthcare
+ Management and manufacturing
+ World Wide Web
+ Security

Implications
+ Philosophical foundations
+ Social impact and ethics
+ Evaluation of AI systems
+ AI education


DATES

+ Abstract registration: 14 July, 2017
+ Submission: 21 July, 2017
+ Notification: 18 August, 2017
+ Final version: 25 August, 2017
+ Early registration deadline: tba
+ Conference: 19-22 October, 2016


SUBMISSION and PUBLICATION

Submission is via EasyChair at
    https://easychair.org/conferences/?conf=gcai2017
The proceedings will be published by EasyChair Publications in the EPiC Series
in Computing. The volume will be open access and authors will retain copyright.


INVITED SPEAKERS

+ Catherine Pelachaud, Telecom-ParisTech, France
+ Marijn Heule, University of Texas at Austin, USA
+ Guy van den Broeck, UCLA, USA


PROGRAMME COMMITTEE

Jose Julio Alferes (Universidade NOVA de Lisboa)
Elisabeth Andre (Augsburg University)
Serge Autexier (DFKI)
Peter Baumgartner (National ICT Australia)
Christoph Benzmueller (Freie Universitaet Berlin) - chair
Philippe Besnard (CNRS / IRIT)
Richard Booth (Cardiff University)
Krysia Broda (Imperial College)
Walter Carnielli (Centre for Logic, Epistemology and the History of Science - CLE)
Amedeo Cesta (CNR - National Research Council of Italy)
Gabriella Cortellessa (CNR-ISTC, National Research Council of Italy)
Mehdi Dastani (Utrecht University)
James Delgrande (Simon Fraser University)
Wolfgang Faber (University of Huddersfield)
Germain Forestier (Universite de Haute Alsace)
Gerhard Friedrich (Alpen-Adria-Universitaet Klagenfurt)
Thom Fruehwirth (University of Ulm)
Daniel Garijo (UCLA)
Marco Gavanelli (University of Ferrara)
Gianluigi Greco (University of Calabria)
Ian Horswill (Northwestern University)
Katsumi Inoue (NII)
Mateja Jamnik (University of Cambridge)
Ernesto Jimenez-Ruiz (University of Oxford)
Tommi Junttila (Aalto University)
Panagiotis Kanellopoulos (University of Patras and CTI "Diophantus")
Gabriele Kern-Isberner (Technische Universitaet Dortmund)
Roman Kontchakov (Birkbeck, University of London)
Tim Landgraf (Freie Universitaet Berlin)
Jerome Lang (CNRS, LAMSADE, Universite Paris-Dauphine)
Gang Li (School of Information Technology, Deakin University)
Sanjiang Li (University of Technology Sydney)
Christine Lisetti (Florida International University) - chair
Xudong Luo (Guangxi Normal University)
Ines Lynce (INESC-ID/IST, Universidade de Lisboa)
Ana Gabriela Maguitman (Universidad Nacional del Sur)
George Metcalfe (University of Bern)
Angelo Montanari (University of Udine)
Till Mossakowski (University of Magdeburg)
Xavier Parent (University of Luxembourg)
Radu-Emil Precup (Politehnica University of Timisoara)
Dumitru Roman (SINTEF / University of Oslo)
Marco Roveri (FBK-irst)
Steven Schockaert (Cardiff University)
Magy Seif El-Nasr (Northeastern University)
Christine Solnon (LIRIS CNRS UMR 5205 / INSA Lyon)
Daria Stepanova (Max Planck Institute for Informatics)
Thomas Stuetzle (Universite Libre de Bruxelles (ULB))
Martin Theobald (Universite du Luxembourg) - chair
Juergen Umbrich (Vienna University of Economy and Business (WU))
Maria Esther Vidal (Universidad Simon Bolivar, Dept. Computer Science)
Inon Zuckerman (Ariel University)

[Caml-list] parany: a minimalistic library to parallelize any kind of computation

[Francois BERENGER]

Dear caml riders,

I am pleased to announce parany, a kind of minimalistic and more generic 
version of parmap.

Yes, a minimalistic version of parmap is possible! :D

Parany can be found here:

https://github.com/UnixJunkie/parany

The super simple interface is:
---
(* the demux function must throw End_of_input once it's done *)
exception End_of_input

val run: nprocs:int ->
          demux:(unit -> 'a) ->
          work:('a -> 'b) ->
          mux:('b -> unit) -> unit
---

This is a beta release, so please don't expect excellent performance and 
rock stability. Also, maybe it can crash in some cases (tell me).

The difference with parmap is that parany is supposed to be able
to work with very large files (that you cannot load in memory at once)
or infinite streams of things to process.

Managing such cases is doable with parmap but requires some programming
and is not optimal in terms of parallelization performance (you have to 
stop all work when loading in memory a part of your file and
fork all your workers again after that).

Parany relies on the shared data structure Netmcore_queue from
Gerd Stolpmann's excellent ocamlnet library to take care of all the magic.

Contributions are welcome to improve performance and stability, while 
not degrading code quality.

Also, since this is a minimalistic library, I am not sure
new features will be accepted. ;)

If there is some interest, I can put it into opam, let me know.

Regards,
F.

[Caml-list] [ANN] first release of cpm: the Classification Performance Metrics library

[Francois BERENGER]

O Caml riders,

It is my pleasure to announce the first release of cpm.

cpm allows to compute various classification performance metrics, like:
- area under the ROC curve (AUC)
- BEDROC (Bolzmann Enhanced Discrimination of the ROC curve)
- Power Metric (PM) at given threshold
- Enrichment Factor (EF) at given percentage

Here is an example use:
---
(* first, define your score_label module *)
module SL = struct
   type t = string * float * int * bool
   let get_score (_, s, _, _) = s
   let get_label (_, _, _, l) = l
end

(* second, instantiate the ROC functor for your score_label module *)
module ROC = MakeROC.Make (SL)

(* third, call any classification performance metric you need *)
[...]
let auc = ROC.auc scores in
[...]
---

The score is the output of your predictor.
For a true positive, the label must be 1.
For a true negative, the label must be 0.
Your predictor is supposed to give high scores to true positives
and low scores to true negatives.

The code is here:
https://github.com/UnixJunkie/cpmlib

The library should be available shortly in opam under the name cpm.

For those who like to read, here are some interesting reads on related 
subjects:
- https://jcheminf.springeropen.com/articles/10.1186/s13321-016-0189-4
- 
https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btq140
- http://pubs.acs.org/doi/abs/10.1021/ci600426e

Have fun classifying,
F.

[Caml-list] new release of parany (1.0.2): a minimalistic OCaml library to parallelize any kind of computation

[Francois BERENGER]

Dear caml riders,

There is a new version of parany available in opam: 1.0.2.

I use parany intensively these days and have not seen it crash, so it
might be ready for production use.
My results are equal in the case of a parallel or a sequential run.

Note to potential users: parany doen't try to preserve the order
of the elements it processes in parallel (to maximize performance).
The elements to process must be independent (same thing if you were 
using parmap).

The code is here:
https://github.com/UnixJunkie/parany

Here are some parallelization performance results on a real use case:
---
#nprocs med_processing_frequency_5runs(Hz) theoric_max(Hz) efficacy(%)
1 20.1996 20.1996 1.00
2 39.7312 40.3992 0.98
3 52.5495 60.5988 0.87
4 75.1963 80.7984 0.93
5 87.5909 100.9980 0.87
6 107.1065 121.1976 0.88
7 118.8431 141.3972 0.84
8 137.8433 161.5967 0.85
9 148.3669 181.7963 0.82
10 164.9220 201.9959 0.82
11 176.0519 222.1955 0.79
12 192.4726 242.3951 0.79
13 198.2970 262.5947 0.76
14 213.8255 282.7943 0.76
15 224.0193 302.9939 0.74
16 232.4273 323.1935 0.72
---

In this case, with up to four cores, the parallelization performance
is excellent. Efficacy = 1.0 cannot be reached once nprocs > 1
due to Amdahl's law.

The granularity of the computation in my experiment was ~= 0.05s of
CPU time per element in my input file.
So, I guess you might get similar or even better parallelization 
performance if your processing time per element is higher than this.

You can send me a quick email if parany is useful to you.

Happy number crunching,
F.