Program
Conference Program
AI 2015 – Schedule of Events
Date | Event |
---|---|
November 30, 2015 | Doctoral Consortium |
December 1, 2015 | Workshop and Tutorial |
December 2-4, 2015 | Conference |
Conference Schedule is available download as a PDF file HERE, and it is also accessible by CONFERENCEDAY APP.
For iPhone: click here
For Android: click here
The online proceedings of AI 2015 is available here
Workshops and Tutorials
Tuesday, 1st December
|
|||
---|---|---|---|
Room | |||
Time | Studio 1 | Combined Studio 2-3 | Studio 4 | 8:00- |
Registration
|
9:00-10:30 | Tutorial: Deep Learning | ||
10:30-11:00 |
Morning Tea Level 1 Foyer
|
||
11:00-12:30 | Workshop: KR Conventicle 2015 - In memory of Prof. Norman Foo (1943 – 2015) | Workshop: Deep Learning and its Applications in Vision and Robotics | Tutorial: Mathematical Optimization in Supply Chain Logistics |
12:30-14:00 |
Lunch Level 1 Foyer
|
||
14:00-15:30 | Tutorial: Fundamentals of Computational Social Choice | ||
15:30-16:00 |
Afternoon Tea Level 1 Foyer
|
||
16:00-17:30 | Tutorial: A Data Analytics View of Genomics |
Conference
Wednesday, 2nd December
|
|||
---|---|---|---|
Conference Stream | |||
A
|
B
|
||
Ballroom 2
|
Ballroom 3
|
||
Time | |||
8:00- | Registration | ||
8:50-9:00 | Opening | Conference Opening | |
9:00-10:00 | Keynote | Toby Walsh | |
10:00-10:30 | Morning Tea |
Level 1 Foyer
|
|
10:30-12:15 | Session 1 | Data Analytics | Social Aspects of AI |
12:15-14:00 | Lunch |
Capitol Grill restaurant, QT ground floor
|
|
14:00-15:30 | Session 2 | Machine Learning 1 | Knowledge Representation 1 |
15:30-16:00 | Afternoon Tea |
Level 1 Foyer
|
|
16:00-17:30 | Session 3 | Machine Learning 2 | Knowledge Representation 2 |
Thursday, 3rd December
|
|||
Conference Stream | |||
A | B | ||
Ballroom 2 | Ballroom 3 | ||
Time | |||
8:45- | Registration | ||
9:00-10:00 | Keynote | Wolfram Burgard | |
10:00-10:30 | Morning Tea |
Level 1 Foyer
|
|
10:30-12:15 | Session 4 | Social Networks | Knowledge Representation 3 |
12:15-14:00 | Lunch |
Capitol Grill restaurant, QT ground floor
|
|
14:00-15:30 | Session 5 | Evolutionary algorithms | Agents |
15:30-16:00 | Afternoon Tea |
Level 1 Foyer
|
|
16:00-17:40 | Session 6 | Search | Robotics and Automation (joint with ACRA) |
18:30- | Dinner |
National Museum of Australia
|
|
Friday, 4th December
|
|||
Conference Stream | |||
A | B | ||
Ballroom 2 | Ballroom 3 | ||
Time | |||
8:45- | Registration | ||
9:00-10:00 | Keynote | Kate Smith Miles | |
10:00-10:30 | Morning Tea |
Level 1 Foyer
|
|
10:30-11:45 | Session 7 | Machine Learning 3 | Knowledge Representation 4 |
12:00-14:00 | Lunch |
QT VIP Lounge
|
|
14:00-16:00 | Closing Session |
Social gathering in the QT VIP Lounge
|
Workshops
- Deep Learning and its Applications in Vision and Robotics, Organised by Juxi Leitner (QUT), Anoop Cherian (ANU), and Sareh Shirazi (QUT)
- KR Conventicle 2015 - In memory of Prof. Norman Foo (1943 - 2015)
Tutorials
- Deep Learning by Dr. Lizhen Qu
- Mathematical Optimization in Supply Chain Logistics, by Thomas Kalinowski
- Fundamentals of Computational Social Choice, by Haris Aziz and Nicholas Mattei
- A Data Analytics View of Genomics, by Cheng Soon Ong
Keynote Presentations
- Professor Toby Walsh, University of New South Wales – Profile
- Professor Wolfram Burgard, Albert-Ludwigs-Universität Freiburg – Profile
- Professor Kate Smith Miles, Monash University – Profile
Conference Sessions
Session 1A
77 | L | Ahmad Shahi, Brendon Woodford and Jeremiah Deng | Event Classification using Adaptive Cluster-Based Ensemble Learning of Streaming Sensor Data |
7 | L | Ling Luo, Wei Liu,Irena Koprinska and Fang Chen | Discovering Causal Structures from Time Series Data via Enhanced Granger Causality |
55 | L | Dang Nguyen, Wei Luo, Dinh Phung and Svetha Venkatesh | Understanding toxicities and complications of cancer treatment: A data mining approach |
91 | S | Yuan Jin and Grace Rumantir | A Two Tiered Finite Mixture Modelling Framework to Cluster Customers on EFTPOS Network |
46 | S | Markus Lumpe and Quoc Bao Vo | Finding the k in K-means Clustering: A Comparative Analysis Approach |
Session 1B
87 | L | Shogo Higuchi, Ryohei Orihara, Yuichi Sei, Yasuyuki Tahara and Akihiko Ohsuga | Decision Making Strategy Based on Time Series Data of Voting Behavior |
34 | L | Dirk Pattinson and Carsten Schuermann | Vote Counting as Mathematical Proof |
53 | L | Guifei Jiang, Dongmo Zhang and Laurent Perrussel | Knowledge Sharing in Coalitions |
71 | S | Michael Siers and Md Zahidul Islam | Standoff-Balancing: A novel class imbalance treatment method inspired by military strategy |
48 | S | Chaiwat Thawiworadilok, Mohsen Jafari Songhori and Takao Terano | Investigating Japanese Ijime (bullying) behaviour using Agent-Based and System Dynamics Models |
Session 2A
35 | L | Sam Fletcher and Md Zahidul Islam | A Differentially Private Random Decision Forest using Reliable Signal-to-Noise Ratios |
56 | L | Keith Johnson and Wei Liu | A dual network for transfer learning with spike train data |
54 | L | Fenglu Ge, Wayne Moore and Michael Antolovich | Learning from Demonstration using GMM, CHMM and DHMM: A Comparison |
75 | S | Liyuan Zhou andHanna Suominen | Information Extraction to Improve Standard Compliance: The Case of Clinical Handover |
Session 2B
30SDavid BillingtonA Propositional Plausible Logic
12 | L | Karsten Martiny andRalf Möller | Abduction in PDT Logic |
80 | L | Francis Li, Jesse Frost and Braden J. Phillips | An Episodic Memory Retrieval Algorithm for the Soar Cognitive Architecture |
41 | L | Rajeev Gore, Jason Li and Thomas Pagram | Implementing Modal Tableaux using Sentential Decision Diagrams |
Session 3A
70 | L | Kylie Chen, Yun Sing Koh and Patricia Riddle | Tracking Drift Severity in Data Streams |
82 | L | Teo Susnjak, David Kerry, Andre L. C. Barczak, Napoleon Reyes and Yaniv Gal | Wisdom of Crowds: An Empirical Study of Ensemble-based Feature Selection Strategies |
43 | L | Iman Kamkar, Sunil Gupta, Dinh Phungand Svetha Venkatesh | Stable Feature Selection with Support Vector Machines |
72 | S | Shinichi Yamada, Kourosh Neshatian and Raazesh Sainudiin | Optimal Hyper-parameter Search in Support Vector Machines Using Bezier Surfaces |
Session 3B
36 | L | Özgür Lütfü Özcep | A Representation Theorem for Spatial Relations |
14 | L | Frederic Maire and Gavin Suddrey | Path Algebra for Mobile Robots |
68 | L | Ranjini Swaminathan, Mohan Sridharan, Gillian Dobbie and Katharine Hayhoe | Modeling Ice Storm Climatology |
21 | S | Jun Hou, Ruth Schulz, Gordon Wyeth and Richi Nayak | Finding Within-Organisation Spatial Information on the Web |
Session 4A
88 | S | Tomoaki Ueda,Ryohei Orihara,Yuichi Sei, Yasuyuki Tahara and Akihiko Ohsuga | Towards the Elimination of the Miscommunication between Users in Twitter : Tweet classification based on expected responses by user |
18 | L | Alphan Culha andAndrew Skabar | Graph-based Collaborative Filtering using Rating Nodes: a Solution to the High Ratings/Low Ratings Problem |
57 | L | Sharon Torao-Pingiand Richi Nayak | Understanding People Relationship: Analysis of Digitised Historical Newspaper Articles |
85 | L | Ahmad Abdel-Hafez and Yue Xu | Exploiting the Beta Distribution-Based Reputation Model in Recommender System |
10 | S | Parma Nand, Rivindu Perera and Gisela Klette | A Tweet Classification Model Based on Dynamic and Static Component Topic Vectors |
Session 4B
26 | S | Rivindu Perera and Parma Nand | Answer Presentation with Contextual Information: A Case Study using Syntactic and Semantic Models |
52 | L | Jiewen Wu, Taras Kinash, David Tomanand Grant Weddell | Absorption for ABoxes and TBoxes with General Value Restrictions |
49 | L | Franz Baader, Stefan Borgwardt and Marcel Lippmann | Temporal Conjunctive Queries in Expressive Description Logics with Transitive Roles |
51 | L | David Toman andGrant Weddell | On the Krom Extension of CFDInc |
78 | S | Özgür Lütfü Özcep,Ralf Möller and Christian Neuenstadt | Stream-Query Compilation with Ontologies |
Session 5A
97 | L | Kavitesh Bali andRohitash Chandra | Scaling up Multi-Island Competitive Cooperative Coevolution for Real Parameter Global Optimization |
45 | L | Erandi Lakshika, Michael Barlow and Adam Easton | Evolving High Fidelity Low Complexity Sheepdog Herding Simulations Using a Machine Learner Fitness Function Surrogate for Human Judgement |
3 | L | Kalyan Shankar Bhattacharjee and Tapabrata Ray | An Evolutionary Algorithm with Classifier Guided Constraint Evaluation Strategy for Computationally Expensive Optimization Problems |
79 | S | Shanjida Khatun, Hasib Ul Alam,Mahmood A Rashidand Swakkhar Shatabda | GeneTransfer: A Novel Genetic Operator for Discovering Diverse-Frequent Patterns |
Session 5B
92 | L | Satyendra Singh Chouhan and Rajdeep Niyogi | DMAPP: A Distributed Multi-Agent Path Planning Algorithm |
31 | L | Fenghui Ren, Minjie Zhang and Chao Yu | A Multi-Agent Approach for Decentralized Voltage Regulation by Considering Distributed Generators |
28 | L | Chao Yu, Hongtao Lv, Fenghui Ren, Honglin Bao and Jianye Hao | Hierarchical Learning for Emergence of Social Norms in Networked Multiagent Systems |
40 | S | Aodah Diamah, Michael Wagner and Menkes van den Briel | A comparative study on vector similarity methods for offer generation in multi-attribute negotiation |
Session 6A
22 | L | Cameron Browne and Frederic Maire | Monte Carlo Analysis of a Puzzle Game |
100 | S | Rubai Ameen and Sameer Alam | A Heuristic Search Approach to find Contrail Avoidance Flight Routes |
38 | S | Tom Everitt andMarcus Hutter | Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part I: Tree Search |
39 | L | Tom Everitt andMarcus Hutter | Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part II: Graph Search |
Session 6B
32 | L | Reza Farid | Region-Growing Planar Segmentation for Robot Action Planning |
59 | S | Frederic Maire, Luis Mejias Alvarez and Amanda Hodgson | Automating Marine Mammal Detection in Aerial Images Captured During Wildlife Surveys: a Deep Learning Approach |
63 | S | Manisha Senadeera, Frederic Maire and Andry Rakotonirainy | Turning Gaming EEG Peripherals into Trainable Brain Computer Interfaces |
S | ACRA TBD | ||
S | ACRA TBD | ||
S | ACRA TBD |
Session 7A
23 | L | Peter Vamplew, Rustam Issabekov, Richard Dazeley and Cameron Foale | Reinforcement Learning of Pareto-Optimal Multiobjective Policies Using Steering |
4 | L | Kalyan Shankar Bhattacharjee and Tapabrata Ray | Cost to evaluate versus Cost to learn ? Performance of selective evaluation strategies in Multiobjective Optimization |
33 | L | Adam Klyne and Kathryn Merrick | Task Allocation Using Particle Swarm Optimisation and Anomaly Detection to Generate a Dynamic Fitness Function |
Session 7B
60 | L | Kinzang Chhogyal,Abhaya Nayak and Abdul Sattar | Probabilistic Belief Contraction: Considerations on epistemic entrenchment, probability mixtures and KL divergence |
15 | L | Yifan Jin, Kewen Wang and Zhe Wang | Possibilistic Inferences in Answer Set Programming |
20 | L | Alexander Motzek and Ralf Möller | Exploiting Innocuousness in Bayesian Networks |