Machine Learning Coffee seminar "Learning and Stochastic Control in Gaussian Process Driven Physical Systems"

Lecturer : 
Simo Särkkä
Event type: 
HIIT seminar
Event time: 
2018-02-19 09:15 to 10:00
Place: 
Exactum D123, Kumpula
Description: 

Simo Särkkä, Aalto University

Learning and Stochastic Control in Gaussian Process Driven Physical Systems

Abstract: Traditional machine learning is often overemphasising problems, where we wish to automatically learn everything from the problem at hand solely using a set of training data. However, in many physical systems we already know much about the physics, typically in form of partial differential equations. For efficient learning in this kind of systems, it is beneficial to use gray-box models where only the unknown parts are modeled with data-trained machine learning models. This talk is concerned with learning and stochastic control in physical systems which contain unknown input or force signals that we wish to learn from data. These unknown signals are modeled using Gaussian processes (GP) from machine learning. The resulting latent force models (LFMs) can be seen as hybrid models that contain a first-principles physical model part and a non-parametric GP model part. We present and discuss methods for learning and stochastic control in this kind of models.

Simo Särkkä is an Associate Professor and Academy Research Fellow with Aalto University, Technical Advisor of IndoorAtlas Ltd., and an Adjunct Professor with Tampere University of Technology and Lappeenranta University of Technology. His research interests are in multi-sensor data processing systems with applications in artificial intelligence, machine learning, inverse problems, location sensing, health technology, and brain imaging. He has authored or coauthored around 100 peer-reviewed scientific articles and his book "Bayesian Filtering and Smoothing" along with its Chinese translation were published via the Cambridge University Press in 2013 and 2015, respectively. He is a Senior Member of IEEE and serving as an Associate Editor of IEEE Signal Processing Letters.

Machine Learning Coffee seminars are weekly seminars held jointly by the Aalto University and the University of Helsinki. The seminars aim to gather people from different fields of science with interest in machine learning. Talks will begin at 9:15 am and porridge and coffee will be served from 9:00 am.

Next talks:

  • February 26, Otaniemi: Melih Kandemir "Bayesian Deep Learning for Image Data"
  • March 5, Kumpula: Tuuli Toivonen

Welcome!

Machine Learning Coffee Seminar: "Here Be Dragons: High Dimensional Spaces and Statistical Computations"

Lecturer : 
Michael Betancourt
Event type: 
HIIT seminar
Event time: 
2018-02-12 09:15 to 10:00
Place: 
Lecture room T5, CS building, Konemiehentie 2, Otaniemi
Description: 

Michael Betancourt, Columbia University

Here Be Dragons: High-Dimensional Spaces and Statistical Computation

Abstract: With consistently growing data sets and increasingly complex models, the frontiers of applied statistics is found in high-dimensional spaces. Unfortunately most of the intuitions that we take for granted in our low-dimensional, routine experiences don’t persist to these high-dimensional spaces which makes the development of scalable computational methodologies and algorithms all the more challenging. In this talk I will discuss the counter-intuitive behavior of high-dimensional spaces and the consequences for statistical computation.

Machine Learning Coffee seminars are weekly seminars held jointly by the Aalto University and the University of Helsinki. The seminars aim to gather people from different fields of science with interest in machine learning. Talks will begin at 9:15 am and porridge and coffee will be served from 9:00 am.

Next talk:

February 19, Kumpula: Simo Särkkä

Welcome!

 

Machine Learning Coffee Seminar: "Studying mutational processes in cancer"

Lecturer : 
Ville Mustonen
Event type: 
HIIT seminar
Event time: 
2018-02-05 09:15 to 10:00
Place: 
Exactum D123, Kumpula
Description: 

Ville Mustonen, Professor of Computer Science, University of Helsinki

Studying mutational processes in cancer

Abstract: Somatic mutations in cancer have accumulated during its evolution and are caused by different exposures to carcinogens and therapeutic agents, as well as, intrinsic errors that occur during DNA replication. Analysing a set of cancer samples jointly allows to explain their somatic mutations as a linear combination of (to be learned) mutational signatures. In this presentation I will discuss the problem of learning mutational signatures from cancer data using probabilistic modelling and nonnegative matrix factorisation. I further describe our on going work using mutational signatures in the context of drug response prediction and extensions of the basic model to explicitly include DNA repair processes.

Machine Learning Coffee seminars are weekly seminars held jointly by the University of Helsinki and Aalto University. The seminars aim to gather people from different fields of science with interest in machine learning. Talks will begin at 9:15 am and porridge and coffee will be served from 9:00 am.

Welcome!

Machine Learning Coffee Seminar: "Confident Bayesian Learning of Graphical Models"

Lecturer : 
Mikko Koivisto
Event type: 
HIIT seminar
Event time: 
2018-01-22 09:15 to 10:00
Place: 
Exactum D123, Kumpula
Description: 

Mikko Koivisto, Associate Professor, University of Helsinki

Confident Bayesian Learning of Graphical Models

Abstract: Confident Bayesian learning amounts to computing summaries of a posterior distribution either exactly or with probabilistic accuracy guarantees. I will review the state of the art in confident Bayesian structure learning in graphical models, focusing on the class of Bayesian networks and its subclass of chordal Markov networks.

Machine Learning Coffee seminars are weekly seminars held jointly by the University of Helsinki and Aalto University. The seminars aim to gather people from different fields of science with interest in machine learning. Talks will begin at 9:15 am and porridge and coffee will be served from 9:00 am.

Next talks: 
Jan 22 Kumpula: Mikko Koivisto
Jan 29 Otaniemi: public job talks (details TBA)
Feb 5 Kumpula: Ville Mustonen
Feb 12 Otaniemi: Michael Betancourt

Welcome!

Machine Learning Coffee seminar "Scalable Algorithms for Extreme Multi-Class and Multi-Label Classificiation in Big Data"

Lecturer : 
Rohit Babbar
Event type: 
HIIT seminar
Doctoral dissertation
Respondent: 
Opponent: 
Custos: 
Event time: 
2018-01-15 09:15 to 10:00
Place: 
Lecture room T2, CS building, Konemiehentie 2, Otaniemi
Description: 

Rohit Babbar, Professor of Computer Science, Aalto University

Scalable Algorithms for Extreme Multi-Class and Multi-Lable Classification in Big Data

Abstract: In the era of big data, large-scale classification involving tens of thousand target categories is not uncommon. Also referred to as Extreme Classification, it has also been recently shown that the machine learning challenges arising in ranking, recommendation systems and web-advertising can be effectively addressed by reducing it to extreme multi-label classification framework. In this talk, I will discuss my two recent works, and present TerseSVM and DiSMEC algorithms for extreme multi-class and multi-label classification. The precision@k and nDCG@k results using DiSMEC improve by upto 20% on benchmark datasets over state-of-the-art methods, which are used by Microsoft in production system of Bing Search. The training process for these algorithms makes use of openMP based distributed architectures, and is able to leverage thousands of cores for computation.

Machine Learning Coffee seminars are weekly seminars held jointly by the Aalto University and the University of Helsinki. The seminars aim to gather people from different fields of science with interest in machine learning. Talks will begin at 9:15 am and porridge and coffee will be served from 9:00 am.

Next talk:

January 22, Kumpula: Mikko Koivisto

Welcome!

 

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