Lund Connected Systems and Circuit Design Workshop 2019
Welcome to the 2019 Lund Connected Systems and Circuit Design Workshop
When: September 19-20, 2019
September 19: Grand Hotel, Lund
September 20: LTH, Lund University Lund, Sweden
The workshop will offer an overview of research activities in IC design and realted areas at Lund University. Additionally, invited presentations on related subjects will be given by outstanding experts from both academia and industry.
The workshop is hosted by the
Lund University Excellence Center in System Design on Silicon (SoS).
The workshop is free of charge!
Registration information will appear!
|When:||2019-09-19 09:00 to 2019-09-20 15:00|
|Location:||Grand Hotel day 1, LTH day 2|
AIML@LU WS: AI & ML Technologies
This AIML@LU fika-to-fika workshop focuses on the development of the technologies that form the basis of Artificial Intelligence and Machine Learning. Possible topics to discuss are the research front for different types of AI, but also to look at different techniques for machine learning.
When: 30 August at 9.30 - 15.30
Where: MA:6 Annexet*, Sölvegatan 20, Lund, Sweden, LTH, Lund University
9.30 Fika and mingle
10.15 Introduction and update regarding the AIML@LU network
10.30 Ongoing projects
Martin Karlsson, Lund University: Robot Programming by Demonstration Based on Machine Learning
Abstract: Whereas humans would prefer to program on a high level of abstraction, for instance through natural language, robots require very detailed instructions, for instance time series of desired joint torques. In this research, we aim to meet the robots half way, by enabling programming by demonstration.
Marcus Klang, Lund University: Finding Things in Strings
Najmeh Abiri, Lund University: Variational Autoencoders
Joakim Johnander, Linköping University: Deep Recurrent Neural Networks for Video Object Segmentation
Abstract: Given a video with a target or object marked in the first frame, we aim to track and segment the target throughout the video. A fundamental challenge is to find an effective representation of the target and background appearance. In this work, we propose to tackle this challenge by integrating a probabilistic model as a differentiable and end-to-end trainable deep neural network module.
12.00 Lunch and mingle
13.00 Future trends and interesting examples
Mikael Green, Desupervised2: Bayesian Deep Probabilistic Programming: Are we there yet?
Abstract: Not many would argue against the Bayesian paradigm being the most useful one in modeling problems where parameter estimations are inherently uncertain. But unfortunately most interesting models, especially the ones we know from deep learning, have been very hard to fit in any reasonable amount of time. When dealing with +10 million parameters and +100 thousand data points, Markov Chain Monte Carlo just isn't a viable option. This is why almost every practitioner in deep learning defaults to maximum likelihood estimates through optimization via stochastic gradient descent, because it's much faster. In this talk we'll explore a promising way of doing full Bayesian inference on large scale models via stochastic black box variational inference.
Erik Gärtner, Lund University: Intrinsic Motivation - Exploration, curiosity and learning for learning's sake
Abstract: Humans as well as other animals are curious beings that develop cognitive skills on their own without the need for external goals or supervision.
Inspired by this, how can we encourage AIs to learn and solve tasks by themselves?
This talk presents the fascinating area of intrinsic reward in the context of reinforcement learning by showcasing recent articles and results.
14.30 Summary and conclusions
15.00 Fika and mingel
To participate is free of charge, but please register no later than 28 August 12.00 at: http://aiml.lu.se/events/registration-2019-08-30/
If you have any questions, suggestions or would like to contribute to the program please contact one of:
- Jacek Malec
- Mathias Ohlsson,
- Kalle Åström
- Jonas [dot] Wisbrant [at] cs [dot] lth [dot] se (subject: AIML_WS_11_April_2019) (Jonas Wisbrant)
* Former known as 'Matteannexet'.
|When:||2019-08-30 09:30 to 2019-08-30 15:30|
|Location:||Where: MA:6 Annexet*, Sölvegatan 20, Lund, Sweden, LTH, Lund University|
ELLIIT Distinguished Lecture by Bill Dally: The Future of Computing: Domain-Specific Accelerators
Speaker: Bill Dally, Chief Scientist and Vice President of NVIDIA Research and Inez Kerr Bell Professor of Computer Science and Electrical Engineering at Stanford University
Title of talk: The Future of Computing: Domain-Specific Accelerators
Abstract: Scaling of computing performance enables new applications and greater value from computing. With the end of Moore?s Law and Dennard Scaling, continued performance scaling will come primarily from specialization. Graphics processing units are an ideal platform on which to build domain-specific accelerators. They provide very efficient, high performance communication and memory subsystems - which are needed by all domains. Specialization is provided via ?cores?, such as tensor cores or ray-tracing cores that accelerate specific applications. This talk will describe some common characteristics of domain-specific accelerators via case studies.
|When:||2019-06-19 14:30 to 2019-06-19 15:00|
|Location:||MH:309A, Mattehuset, Sölvegatan 18, Lund|