News
A New Supercomputer for Scaling Up Machine Learning and Artificial Intelligence at Waipapa Taumata Rau / The University of Auckland
The School of Computer Science at Waipapa Taumata Rau / The University of Auckland (UoA), has invested in and installed a new GPU supercomputer, aiming at building capability of large-scale machine learning and artificial intelligence research and teaching. The...
Machine Learning Seminar by Prof. Christian S. Jensen – New Vehicle Routing Paradigms Enabled by Big Vehicle Trajectory Data
Short Bio Christian S. Jensen is Professor of Computer Science at Aalborg University, Denmark. His research concerns primarily analytics, including machine learning, data mining, and query processing, and data management,...
Machine Learning Seminar by Dr. Xia Ning – Deep Generative Models for Molecule Optimization
Short Bio Dr. Xia Ning is an Associate Professor in the Biomedical Informatics Department, and the Computer Science and Engineering Department, The Ohio State University. She received her Ph.D. in Computer Science and...
Machine Learning Seminar by Alex Gavryushkin – Online Algorithms for Evolutionary and Systems Biology
Short Bio Alex Gavryushkin is an associate professor and Rutherford Discovery Fellow at the University of Canterbury, where he leads the Biological Data Science lab, which he founded in 2017. The lab is primarily interested...
Machine Learning Seminar by Pat Langley – Computational Scientific Discovery: Heuristic Search for Communicable Laws and Models
Short Bio Dr. Pat Langley serves as Director of the Institute for the Study of Learning and Expertise and as a Research Scientist at Stanford University's Center for Design Research. He has contributed to AI and cognitive...
ML Student Seminar on Dec 2 2021: Adversarial Learning on Time Series Forecasting
Where and when: Thursday, Dec 2 at 2-3pm in Google Meets (see the calendar invitation for the link) Speaker: Mark Chen, supervised by Joerg Wicker and Gill Dobbie Abstract: Time series forecasting is one of the main topics which involves time series data. It...
AI Reading Group on Nov 25 2021: The neural architecture of language: Integrative modeling converges on predictive processing
Where and when: Thursday, Nov 25 at 2-3pm in Google Meet (see the calendar invite for the link). Abstract The neuroscience of perception has recently been revolutionized with an integrative modeling approach in which computation, brain function, and behavior are...
ML Student Seminar on Nov 18 2021: Beyond Recall: Teaching High Quality Language Models to Generalise to Unseen Compositional Questions
Where and when: Thursday, Nov 18 at 2-3pm in Google Meets (see the calendar invitation for the link) Speaker: Tim Hartill, supervised by Michael Witbrock and Pat Riddle Abstract: Sequence-to-sequence Transformer-based Language Models pretrained on large text...
Machine Learning Seminar by Zachary Lipton – RATT: Leveraging Unlabeled Data to Guarantee Generalization
Short Bio Zachary Chase Lipton is the BP Junior Chair Assistant Professor of Operations Research and Machine Learning at Carnegie Mellon University and a Visiting Scientist at Amazon AI. He directs the Approximately Correct...
ML Student Seminar on Nov 4 2021: New Zealand Bat Audio Analysis
Where and when: Thursday, Nov 4 at 2-3pm in Google Meets (see the calendar invitation for the link) Speaker: Tsz Fung Ip (Roy), Master of Data Science student Abstract: Due to urbanization in the past few decades, various species of bats in New Zealand are facing...
AI Reading Group on Oct 28 2021: The Computational Gauntlet of Human-Like Learning
Where and when: Thursday, Oct 28 at 2-3pm in 303S-561 or Google Meet (see the calendar invite for the link). Abstract In this paper, we pose a challenge for AI researchers: to develop systems that learn in a human-like manner. We briefly review the history of...
ML Student Seminar on Oct 21 2021: Understanding the mechanisms of multiple epidemic waves of COVID-19
Where and when: Thursday, Oct 21 at 2-3pm in Google Meets (see the calendar invitation for the link) Speaker: Johnny Zhu, supervised by Joerg Wicker and Gill Dobbie Abstract: Covid-19 has been raging around the world for more than 20 months. The epidemic has...
Machine Learning Seminar by Harris Lin – Beyond accuracy: what should you ask from a predictive model?
Short Bio Harris Lin is a data scientist from Plant and Food Research, whose team has expertise in computer vision technologies, signal processing from smart sensors, natural language processing, data-driven consumer...
AI Reading Group on Oct 14 2021: A Survey of Heterogeneous Information Network Analysis
Where and when: Thursday, Oct 14 at 2-3pm in Google Meet (see the calendar invite for the link) or 303S-561 if possible. Abstract Most real systems consist of a large number of interacting, multi-typed components, while most contemporary researches model them as...
AI Reading Group on Sep 30 2021: Generative Spoken Language Modeling from Raw Audio
Where and when: Thursday, Sep 30 at 2-3pm in Google Meet (see the calendar invite for the link) Abstract We introduce Generative Spoken Language Modeling, the task of learning the acoustic and linguistic characteristics of a language from raw audio (no text, no...
Machine Learning Seminar by Mengjie Zhang – Evolutionary Machine Learning: Research, Applications and Challenges
Short Bio Mengjie Zhang is a Fellow of Royal Society of New Zealand, a Fellow of IEEE, an IEEE Distinguished Lecturer, currently Professor of Computer Science at Victoria University of Wellington, where he heads the...
ML Student Seminar on Sep 23 2021: Machine learning application in thin-walled structures
Where and when: Thursday, Sep 23 at 2-3pm in Google Meets (see the calendar invitation for the link) Speaker: Arthur (Zhiyuan) Fang, supervised by Dr. Krishanu Roy and Dr. James Lim in the Department of Civil and Environmental Engineering Abstract: Structural...
ML Student Seminar on Sep 9 2021: Machine Learning in Julia
Where and when: Thursday, Sep 9 at 2-3pm in 303S-561 Speaker: Anthony Blaom, https://ablaom.github.io Abstract: Julia is a young but mature programming language which allows one to write fast code fast. Over a two year period, we have developed a Julia toolbox,...
AI Reading Group on Sep 2 2021: Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
Where and when: Thursday, Sep 2 at 2-3pm in 303S-561 Abstract Machine learning methods offer great promise for fast and accurate detection and prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest radiographs (CXR) and chest computed...
ML Student Seminar on Aug 26 2021: Hitting the Target: Stopping Criteria for Active Learning
Where and when: Thursday, Aug 26 at 2-3pm in 303S-561 Speaker: Zac Pullar-Strecker, B.Sc. Student and Research Assistant (for Joerg Wicker) Abstract: Training modern ML models frequently requires large datasets which are expensive and time-consuming to collect....
AI Reading Group on Aug 19 2021: Tabular Data: Deep Learning is Not All You Need
Where and when: Thursday, Aug 19 at 2-3pm in 303S-561 Abstract A key element of AutoML systems is setting the types of models that will be used for each type of task. For classification and regression problems with tabular data, the use of tree ensemble models...