Computer Science News
Best Paper Award at ACM Mobihoc 2024
A paperLink opens in a new window co-authored by Arpan MukhopadhyayLink opens in a new window has received the Best Paper Award at ACM Mobihoc 2024Link opens in a new window. Mobihoc is a premier international conference on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing. The other authors in the paper are Samira Ghanbarian (uWaterloo), Ravi R. Mazumdar (uWaterloo), and Fabrice Guillemin (Orange Labs, France).
The paper addresses the problem of optimally allocating processors to parallelisable tasks having arbitrary concave speed-up functions. In general, determining the optimal number of processors to allocate to each task in an online fashion is a hard problem since allocating too many processors to one job will make those processors unavailable to other jobs whereas allocating too few processors will result in a small speed-up for the job. The paper proposes a simple randomised algorithm for determining the optimal number of processors to allocate to each job without requiring preemption (or repacking). It shows that the proposed algorithm is asymptotically optimal as the number of processors becomes large (which is often the case in modern clouds) and is also robust to variations in the job size distribution. This is the first time such an algorithm has been found in the literature.
Eight papers accepted to NeurIPS 2024
Eight papers authored by Computer Science researchers from Warwick have been accepted for publication at the 38th Conference on Neural Information Processing Systems, the leading international venue for machine learning research, which will be held on 10-15 December 2024 in Vancouver, British Columbia, Canada:
- Generating Origin-Destination Matrices in Neural Spatial Interaction Models, by Ioannis Zachos, Mark Girolami, and Theodoros Damoulas
- Interventionally Consistent Surrogates for Complex Simulation Models, by Joel Dyer, Nicholas Bishop, Yorgos Felekis, Fabio Massimo Zennaro, Ani Calinescu, Theodoros Damoulas, and Michael Wooldridge
- Learning the Expected Core of Strictly Convex Stochastic Cooperative Games, by Phuong Nam Tran, The Anh Ta, Shuqing Shi, Debmalya Mandal, Yali Du, and Long Tran-Thanh
- Physics-Informed Variational State-Space Gaussian Processes, by Oliver Hamelijnck, Arno Solin, and Theodoros Damoulas
- SARAD: Spatial Association-Aware Anomaly Detection and Diagnosis for Multivariate Time Series, by Zhihao Dai, Ligang He, Shuanghua Yang, and Matthew Leeke
- Symmetric Linear Bandits with Hidden Symmetry, by Phuong Nam Tran, The Anh Ta, Debmalya Mandal, and Long Tran-Thanh
- The Effectiveness of Surprisingly Popular Voting with Partial Preferences, by Hadi Hosseini, Debmalya Mandal, and Amrit Puhan
- What makes unlearning hard and what to do about it, by Kairan Zhao, Meghdad Kurmanji, George-Octavian Bărbulescu, Eleni Triantafillou, and Peter Triantafillou
PhD Studentship in the topic of Multiagent Systems and related areas
We are seeking PhD candidates in the topic of Multiagent Systems and related areas, with particular emphasis on one or more of: computational social choice, algorithmic game theory, multiagent learning, and social and economic networks. The multiagent systems researchers at University of Warwick include Markus Brill, Debmalya Mandal, Ramanujan Sridharan, Long Tran-Thanh, and Paolo Turrini.
The expected starting date is October 2025 or as soon as possible thereafter. The deadline for our internal application round is 1 November 2024. To apply, please fill out the application form (which will ask you to upload a CV and a letter of motivation). We aim to have interviews between November 11th and 22nd, 2024. Top-ranked candidates will be put forward for a fully funded position through the Computer Science Centre for Doctoral Training and Research (CDT) by January 15th 2025.
Seven papers accepted to ICML 2024
Seven papers authored by Computer Science researchers from Warwick have been accepted for publication at the 41st International Conference on Machine Learning, one of the top three global venues for machine learning research, which will be held on 21-27 July 2024 in Vienna, Austria:
- Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs, by Stelios Triantafyllou, Aleksa Sukovic, Debmalya Mandal, and Goran Radanovic
- Dynamic Facility Location in High Dimensional Euclidean Spaces, by Sayan Bhattacharya, Gramoz Goranci, Shaofeng Jiang, Yi Qian, and Yubo Zhang (Accepted as a spotlight, among the top 13 percent of all accepted papers)
- High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization, by Yihang Chen, Fanghui Liu, Taiji Suzuki, and Volkan Cevher
- Revisiting character-level adversarial attacks, by Elias Abad Rocamora, Yongtao Wu, Fanghui Liu, Grigorios Chrysos, and Volkan Cevher
- Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences, by Andi Nika, Debmalya Mandal, Parameswaran Kamalaruban, Georgios Tzannetos, Goran Radanovic, and Adish Singla
- To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models, by George-Octavian Bărbulescu and Peter Triantafillou
- Towards Neural Architecture Search through Hierarchical Generative Modeling, by Lichuan Xiang, Łukasz Dudziak, Mohamed Abdelfattah, Abhinav Mehrotra, Nicholas Lane, and Hongkai Wen
Digitally Empowering Young People: The Podcast
“Digitally Empowering Young People: The Podcast” is a ground-breaking podcast series hosted by Dr. Roxanne BibizadehLink opens in a new window.
In this inaugural series, we delve into the pressing issue of technology-assisted child sexual abuse material, focusing particularly on the misleading term “self-generated”, which problematically places the blame on the victim. Through this series, we aim to raise awareness and spark vital conversations among educators, parents/carers, law enforcement agencies and professionals working with young people.
Each episode features a distinguished expert voice, offering invaluable insights and perspectives on this critical issue. Contributors include esteemed organisations such as the Internet Watch Foundation, Marie Collins Foundation, National Policing Vulnerable Knowledge and Practice Programme, Parent Zone, Kent County Council, and Voice Box.
Our final episode is created especially for young people, providing them with essential information and resources to navigate the digital landscape safely and responsibly.
To listen to our podcast series, visit us on Spotify: https://open.spotify.com/show/3OANje22oUK5X641ACmxZOLink opens in a new window
For more information about this project and to stay updated on our latest initiatives, please visit our website: www.deyp.orgLink opens in a new window
We’re proud to announce that this project is funded by the ESRC IAA.
Latest academic promotions
We are happy to announce four promotions in the department:
- Dr Charilaos Efthymiou has been promoted to Associate Professor
- Dr Igor Carboni Oliveira has been promoted to Associate Professor
- Dr Hongkai Wen has been promoted to Professor
- Dr Weiren Yu has been promoted to Associate Professor
Many congratulations to our colleagues for all their achievements!
Paris Giampouras joins the department as an Assistant Professor
We are happy to announce that Dr Paris Giampouras has joined the Department of Computer Science as an Assistant Professor. Originally from Greece, he has relocated to Warwick from Baltimore, where he spent four years working as a Postdoctoral Fellow and later as a Research Faculty member at the Mathematical Institute for Data Science at Johns Hopkins University. His expertise lies in machine learning theory and its applications in image processing and computer vision. More specifically, his research has focused on exploring parsimonious representations to address various inverse problems and adversarial robustness.
Currently, he is focusing on two main areas: a) leveraging structured representation in Generative AI applications, and b) developing algorithms that enable continual learning of various tasks for deep learning systems. His goal is to contribute to the foundational understanding of AI algorithms, with a focus on robustness, applications of AI in medicine, and climate change.
We welcome him to the department!