Parallelism in Knowledge Transfer
Organizer(s):
Abhishek Gupta, Amiram Moshaiov, Yaochu Jin
Abstract:
The utilization of knowledge from past experiences is common to the process of learning and to problem-solving by humans. Inspired by humans, researchers in computational intelligence have been developing transfer learning and transfer optimization techniques (TL&TO). TL refers to transfer of knowledge in machine learning techniques to improve performance under limited training data, whereas TO refers to such transfer for accelerating convergence rates in the search for optimal solutions under some criteria. In the last two decades various TL techniques have been studied and their effectiveness has been demonstrated over a large set of problems. This success has been followed with similar attempts in the area of TO, with a particular emphasis on population based bio-inspired optimization approaches. The main goal of this workshop is to provide a meeting place for PPSN participants who are interested in research on bio-inspired TL&TO techniques. We aim to discuss current research on the development of such techniques and on their real-life applications. Finally, we expect to suggest future research directions for TL&TO.
External webpage of workshop:
https://www.eng.tau.ac.il/~moshaiov/Transfer_WS_Webpage.html
Good Benchmarking Practices for Evolutionary Computation
Organizer(s):
Boris Naujoks, Benjamin Doerr, Carola Doerr, Pascal Kerschke, Olaf Mersmann, Mike Preuss
Abstract:
Benchmarking plays a vital role in understanding the performance and search behavior of sampling-based optimization techniques such as evolutionary algorithms. This workshop will continue our workshop series on good benchmarking practices at different events in the context of EC that we started in 2020. The core theme is on benchmarking evolutionary computation methods and related sampling-based optimization heuristics, but each year, the focus is changed.
The focus of our PPSN 2022 workshop will be benchmarking as a mean to fill the gap between theory and practice, e.g., for:
- illustrating findings that have so-far been communicated only towards a mathematically trained audience
- testing the generalization abilities of theoretical results
- deriving empirical insights that can inspire or guide new theoretical investigations
- using theory-derived results as baselines (‘ground truth’) for benchmarking in evolutionary computation and beyond
External webpage of workshop:
https://sites.google.com/view/benchmarking-network/home/activities/ppsn-2022-workshop
Data Science, Machine Learning and Optimization in Support of the Society of the Future
Organizer(s):
Rohit Salgotra, Alma Rahat, Amiram Moshaiov
Abstract:
Our societies are facing arduous global challenges to sustain and develop our civilisations. The development of new dedicated Intelligent Decision-Support Systems (IDSSs) could help address such challenges. Such developments can benefit from the current capabilities to collect data at an unprecedented level and by the amalgamation of novel techniques from Data Science (DS), Machine Learning (ML), Multi-objective Optimisation (MOO) and Multi-criteria Decision-Analysis/Making (MCDA/MCDM). In this workshop, we aim to actively identify the challenges in developing and deploying IDSSs for the society of the future, and discuss potential avenues to tackle them, with a particular focus on helping the decision-making process of policymakers. We are interested in studies on the development and/or application of computational techniques in the context of societal challenges.
External webpage of workshop:
https://dsmlossf.github.io/
25 Years of LeadingOnes (and Other Great Ideas)
A Scientific Workshop Revisiting Günter Rudolph’s Dissertation
Organizer(s):
Benjamin Doerr, Tobias Glasmachers, Thomas Jansen, Carsten Witt
25 years ago, the doctoral dissertation of Günter Rudolph was published. It contained a huge number of ideas, many of which had a profound influence on the at that time very young field of runtime analyses of evolutionary algorithms. In this scientific workshop, we shall take a new look into this classic work. We will showcase some central ideas and concepts from this dissertation, we will discuss what follow-up works they triggered and what are the current best approaches to these problems today, and we will highlight the main open questions related to these topics.
External webpage of workshop:
https://people.compute.dtu.dk/cawi/ppsn-22-workshop-25-years-leadingones.html