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Past KEPACoffee Meetings

The past KEPACoffee meetings are recorded here.

Schedule Spring 2021

During the autumn we have our weekly meetings on Tuesday 1-3PM. If you cannot make it to your own session, please swap places with another group member.

Date Journal club leader Paper (or Topic) Note
26.01 Eric Feature-based molecular networking in the GNPS analysis environment -
02.02 Tianduanyi Prediction of drug combination effects with a minimal set of experiments -
09.02 Minna Comprehensive prediction of secondary metabolite structure and biological activity from microbial genome sequences -
16.02 Juho Fast differentiable sorting and ranking. In International Conference on Machine Learning -
23.02 Sandor The influence of the theory of computation on learning -
02.03 Riikka A Convex Parametrization of a New Class of Universal Kernel Functions -
09.03 Maryam Deep reinforcement learning for the control of microbial co-cultures in bioreactors -
16.03 Eric Research update presentation: Structured Support Vector Machines for LC-MS2 data processing -
23.03 Tianduanyi Drug combination prediction: current project and future perspectives -
30.03 Ankita FIMM Rotation Project Presentation -
06.04 Juho Presentation on Result Visualisation in Papers -
13.04 Minna Final Master's thesis presentation -
20.04 Sandor -
27.04 Riikka -
04.05 Maryam Multi-Agent Determinantal Q-Learning -
11.05 Eric -
18.05 Tianduanyi -
25.05 Taneli Presentation about his PhD work -
01.06 Sandor -

Schedule Autumn 2020

During the autumn we have our weekly meetings on Friday 1-3PM. If you cannot make it to your own session, please swap places with another group member.

Date Journal club leader Paper (or Topic) Note
18.08 Riikka Partial trace regression and low-rank Kraus decomposition -
25.08 Wen Summary of the work as summer intern -
04.09 Eric Kernels for Sequentially Ordered Data -
11.09 Maryam Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning -
18.09 Tianduanyi Review on the drug combination tensor learning project -
25.09 Amir Safe Model-based Reinforcement Learning with Stability Guarantees -
02.10 Juho Ion mobility collision cross-section atlas for known and unknown metabolite annotation in untargeted metabolomics -
09.10 Sandor Kernels on Direct Sum of Vector Spaces -
16.10 Riikka Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust Losses -
23.10 Maryam skipped -
30.10 Eric In Silico Optimization of Mass Spectrometry Fragmentation Strategies in Metabolomics -
06.11 Tianduanyi Research project presentation. -
13.11 - -
20.11 Amir Algorithms for CVaR Optimization in MDPs -
27.11 Lisa Final presentation of her research project: Time-series Analysis for Metabolomics -
04.12 Sandor Presentation: "Optimization as Dynamic Process" (based on this and this paper) -
11.12 Riikka -
18.12 Maryam Shared Experience Actor-Critic forMulti-Agent Reinforcement Learning -

Schedule Spring and Summer 2020

During the summer we have our weekly meetings on Tuesdays 2-4PM only featuring the weekly updates. There is no fixed schedule Journal clubs or presentations.

Date Journal club leader Paper (or Topic) Note
21.01 Maryam Towards a fully automated algorithm drivenplatform for biosystems design -
28.01 Riikka Cross-view kernel transfer -
04.02 Viivi To Understand Deep Learning We Need To Understand Kernel Learning -
11.02 Sandor Presentation: Learning with Manifolds -
18.02 Eric Presentation: MS2 and RT score integration -
25.02 Tianduanyi Research project presentation -
03.03 Juho - Canceled
10.03 Sandor - Canceled
17.03 Maryam - Canceled
24.03 Riikka - Canceled
31.03 Sandor Presentation: Autoencoder and Bottlenecks -
07.04 Juho A consistent regularization approach for structured prediction -
14.04 Maryam Presentation: Reinforcement Learning for Biosystems Design -
21.04 Riikka Interpretable genotype-to-phenotype classifiers with performance guarantees -
28.04 Viivi Tensor Canonical Correlation Analysis for Multi-View Dimension Reduction -
05.05 Eric Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks -
12.05 Tianduanyi -
19.05 Sandor Presentation: Learning Class Relations - Projection Operator Kernel -
26.05 Juho Presentation: Towards Linear Work Multi-output Kernel Machines -
from 05.06 - Only weekly updates

Schedule Autumn 2019

Below is a schedule for the Autumn 2019. If you cannot make it to your own session, please swap places with another group member.

All meetings will be in meeting room B337 on Tuesday from 2-4PM unless otherwise announced.

Date Journal club leader Paper (or Topic) Note
13.08 Juho Brouard et al. Improved Small Molecule Identification through Learning Combinations of Kernel Regression Models. Metabolites, 9(8), p.160. -
20.08 Jane & Aker Summer project presentation -
27.08 Luc & Antoine Summer project presentation Room: A346
03.09 No KEPACOffee -
10.09 Maryam Presentation: Metabolite Network Fine-tuning using Reinforcement Learning -
17.09 Sandor Presentation: Factorization Machines -
24.09 Eric Presentation: Probabilistic Framework for Tandem Mass Spectrometry and Retention Time Data Fusion for Metabolite Identification (Summary of research done in Glasgow) -
01.10 Kai Presentation: Judging the book by it's cover: Dereplicating similar compounds with tandem mass spectrometry -
08.10 Tianduanyi -
15.10 Viivi Memory Efficient Kernel Approximation -
22.10 Juho Distribution-free uncertainty quantification for kernel methods by gradient perturbations -
29.10 Sandor Differentiable Game Mechanics -
05.11 Eric Understanding and correcting pathologies in the training of learned optimizers -
12.11 Maryam Presentation: Metabolite Network Fine-tuning using Reinforcement Learning (an update) -
19.11 Viivi Towards Practical Alternating Least-Squares for CCA -
26.11 - AI DAY
03.12 Tianduanyi -
10.12 Kai Presentation: Classes from Masses -
17.12 Juho Large-Scale Sparse Kernel Canonical Correlation Analysis -

Schedule Spring 2019

Below is a schedule for the Spring 2019. If you cannot make it to your own session, please swap places with another group member.

All meetings will be in meeting room A142 on Wednesday from 4-6PM unless otherwise announced.

Date Journal club leader Paper (or Topic) Note
23.01 Tolou Tensor Canonical Correlation Analysis for Multi-View Dimension Reduction -
30.01 Anna IDG-DREAM Drug-Kinase Binding Prediction Challenge: an update -
06.02 Sandor Presentation: Factorization Machines -
13.02 Markus Presentation: Spectral Kernels -
20.02 Tianduanyi Presentation: Kernel-based Machine Learning Methods for Drug-Target Interaction Prediction -
27.02 Rohit Presentation: Robustness and Extreme Multi-label Classification -
06.03 Heli Master's Thesis Presentation -
13.03 Eric Accelerating Metabolite Identification in Natural Product Research -
20.03 Vilma The re-emergence of natural products for drug discovery in the genomics era -
27.03 Maryam Presentation: Genetic Interventions using Reinforcement Learning -
03.04 Viivi A Linear-Time Kernel Goodness-of-Fit Test -
10.04 Tolou Master's Thesis Presentation -
17.04 Sandor A Theory of Learning with Corrupted Labels -
24.04 Markus - -
01.05 NO MEETING NO MEETING Public Holiday: Vappu
08.05 Maryam Presentation: Research project updates -
15.05 Eric Presentation: Retention Order Prediction using Multiple Kernel Learning -
22.05 Vilma Master's Thesis Presentation -
29.05 - - Only weekly updates!
05.06 Viivi ICML poster pitch rehearsal -
12.06 Heli Presentation: Predictive modeling of anticancer efficacy of drug combinations using factorization machines -
19.06 Anna Results of the IDG-DREAM Drug-Kinase Binding Prediction Challenge -
26.06 Tianduanyi - -

Schedule Autumn 2018

Below is a schedule for the Autumn 2018. If you cannot make it to your own session, please swap places with another group member.

All meetings will be in meeting room B347 on Thursday from 2-4PM unless otherwise announced.

Date Journal club leader Topic Note
16.08 Sandor - -
23.08 Antoine Presentation: Metabolite Identification -
30.08 Celine The weighted Kendall and high-order kernels for permutations. (ICML) -
06.09 Markus - -
13.09 Maryam - -
20.09 Viivi An Adaptive Test of Independence with Analytic Kernel Embeddings room change to A346
27.09 Parisa KONG: Kernels for ordered-neighborhood graphs -
04.10 NO MEETING - CS-Forum held by Anna's opponent
11.10 NO MEETING - CS Research Day from 12-15
18.10 Heli Factorization Machines, Higher-Order Factorization Machines -
25.10 Vilma Presentation: Tandem mass spectra (MS2) to bio-activity prediction -
01.11 Sandor Infinite-Task Learning with RKHSs -
08.11 Markus Presenation: Stein Gradient Descent -
15.11 Maryam e-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem -
22.11 Anna Presenation: Dream Challenge -
29.11 Viivi Stochastic Approximation for Canonical Correlation Analysis -
06.12 NO MEETING - Independence day
13.12 Eric Sparse Learning over Infinite Subgraph Features -
20.12 NO MEETING - -

Schedule Spring 2018

Below is a schedule for the Spring 2018. If you cannot make it to your own session, please swap places with another group member.

All meetings will be in meeting room A142 on Thursday from 2-4PM unless otherwise announced.

Date Leader Event-type Content
25.01 Zheyang Presentation
01.02 Sandor Journal Club, Presentation, ...
08.02 Eric Journal Club, Presentation, ...
15.02 Celine Journal Club, Presentation, ...
22.02 Tolou Presentation
01.03 Anna Journal Club, Presentation, ...
08.03 -- No meeting -- Women in Data Science conference
15.03 Parisa Journal Club, Presentation, ...
22.03 Viivi Journal Club, Presentation, ...
29.03 Markus Journal Club, Presentation, ...
05.04 Sandor Journal Club, Presentation, ...
12.04 Juho Journal Club, Presentation, ...
19.04 Viivi Journal Club, Presentation, ...
26.04 Eric Journal Club, Presentation, ...
03.05 Heli Presentation
10.05 -- No meeting -- -- Ascension day! --
17.05 Parisa Journal Club, Presentation, ...
24.05 Markus Journal Club, Presentation, ...
31.05 Fabio Presentation
07.06 Sandor Journal Club, Presentation, ...
14.06 -- No meeting -- Aalto ceremony week
21.06 -- No meeting -- Eve of midsummer eve
28.06 -- No meeting -- KEPACO Summer retreat

Schedule Autumn 2017

Below is a schedule for the Autumn 2017. If you cannot make it to your own session, please swap places with another group member.

All meetings will be in meeting room B337 on Friday from 2-4PM unless otherwise announced.

Date Leader Event-type Content
25.08 Juho Journal-club Structured Prediction Theory Based on Factor Graph Complexity
01.09 Viivi Presentation Canonical Correlation Methods
08.09 Eric Journal-club Stochastic Structured Prediction under Bandit Feedback
15.09 Sandor Journal-club Kernel functions based on triplet similarity comparisons
22.09 Tolou Presentation Summary of the summer-research
29.09 Heli Journal-club Multiple kernel learning with hybrid kernel alignment maximization
13.10 Celine Presentation Transfer Learning for Metabolite Identification
20.10 Markus Journal-Club
27.10 Sandor Presentation Relational Learning
03.11 Eric Presentation Ranking Support Vector Machine
10.11 Viivi Journal-Club Sparse kernel canonical correlation analysis for discovery of nonlinear interactions in high-dimensional data
17.11 Tolou Journal-Club
24.11 Anna Presentation Drug Target Interaction
01.12 Parisa Presentation
08.12 Celine Journal-Club EasyMKL: a scalable multiple kernel learning algorithm
15.12 Markus Presentation NIPS Overview

Schedule Spring 2017

Date "Pulla" responsible Journal club paper Lead reader
18.01 Eric Dimensionality estimation without distances Linh
25.01 Linh Improved prediction of drug-target interactions using regularized least squares integrating with kernel fusion technique Heli
01.02 1) Sandor Context Sensitive Modeling of Cancer Drug Sensitivity Anna
08.02 1) Celine Topic modeling for untargeted substructure exploration in metabolomics Eric
15.02 Linh Decision theory, reinforcement learning, and the brain Sandor
22.02 1) Huibin (Triton introduction) -
01.03 Anna Gaussian Process Kernels for Pattern Discovery and Extrapolation Markus
08.03 - Kernel manifold alignment for domain adaptation Celine
15.03 1) Mohamed Success based locally weighted multiple kernel combination Anna
22.03 Linh Link prediction in drug-target interactions network using similarity indices Parisa
29.03 Heli Integration of metabolomics, lipidomics and clinical data using a machine learning method Mohamed
05.04 Parisa Tensor-Train Decomposition Linh
12.04 Eric SELF-BLM: Prediction of drug-target interactions via self-training SVM Heli
19.04 Celine Sandor
26.04 Markus Kernel Regression with Order Preferences Eric
03.05 1) Sandor Celine
10.05 Anna Markus
17.05 Parisa -
24.05 Anton Bayesian Mendelian Randomization Anna
31.05 1) Linh Propagation kernels: efficient graph kernels from propagated information Parisa
07.06 1) - -
14.06 Sandor Linh
21.06 Celine Sandor
28.06 Markus Celine
05.07 Anna Markus

Schedule Autumn 2016

Date "Pulla" responsible Journal club paper Lead reader
22.08. Sandor PredRet: Prediction of Retention Time by Direct Mapping between Multiple Chromatographic Systems Eric
29.08. Céline Tensor Decompositions and Application Sandor
05.09. Markus Component-wise kernelized Bayesian matrix factorization Anna
12.09. Sahely Efficient pairwise learning using kernel ridge regression: an exact two-step method Céline
19.09. Viivi The Human Kernel Markus
26.09. Huibin Discriminative Embeddings of Latent Variable Models for Structured Data Sahely
03.10. Anna Canonical Sparse Cross-View Correlation Analysis Viivi
10.10. Parisa A kernel Test of Goodness of Fit Huibin
17.10. Eric Weighted Tanimoto Extreme Learning Machine with Case Study in Drug Discovery Anna
24.10. Linh Localized algorithms for multiple kernel learning Eric
31.10. Sandor Development of a novel fingerprint for chemical reactions and its application to large-scale reaction classification and similarity Parisa
07.11. Sahely Landmarking Manifolds with Gaussian Processes Linh
14.11. Markus Eigenproblems in Pattern Recognition Sandor
21.11. Céline -
28.11. Viivi Markus
05.12. Huibin The multiscale Laplacian graph kernel Céline
12.12. Anna Nonparametric Canonical Correlation Analysis Viivi
19.12. Heli Dual Learning for Machine Translation Huibin

Schedule Spring 2016

Date "Pulla" responsible Journal club paper Lead reader
13.1. Anna Juho
20.1. Celine, Su Computational probing protein-protein interactions targeting small molecules. Bioinformatics 2016 Anna
27.1.(11am) Sandor Convex multi-task learning by clustering, AISTATS 2015 Celine
3.2. Elena
10.2. Sahely Decomposing the tensor kernel support vector machine for neuroscience data with structured labels. Machine learning,2010 Sandor
17.2. Markus Network-Based Drug-Target Interaction Prediction with Probabilistic Soft Logic, by Shobeir Fakhraei, Bert Huang, Louiqa Raschid, and Lise Getoor, IEEE/ACM TCBB 2014 Elena
24.2. Viivi Kernel Extraction via Voted Risk Minimization. NIPS workshop 2015. Sahely
2.3. Huibin Markus
9.3. Eric Greedy Biomarker Discovery in the Genome with Applications to Antimicrobial Resistance. ICML workshop 2015. Viivi
16.3. Maja Convolutional Networks on Graphs for Learning Molecular Fingerprints. NIPS 2015 Huibin
23.3. Linh Support Matrix Machines. ICML 2015 Eric
30.3. Parisa Direct calculation of elementary flux modes satisfying several biological constraints in genome-scale metabolic networks. Bioinformatics 2014. Maja
6.4. Anna Human Action Recognition Based on Context-Dependent Graph Kernels. CVPR 2014. Parisa
13.4. Sandor Safe screening of non-support vectors in pathwise SVM computation. ICML 2013. Linh
20.4. Celine KronRLS-MKL. BMC Bioinformatics 2016. Anna
27.4. Huibin Ensemble of kernel predictors. UAI 2011 Celine
4.5. Sahely Vanishing Component Analysis. ICML 2013. Sandor
11.5. Markus Statistical Model Criticism using Kernel Two Sample Tests. NIPS 2015. Huibin
18.5. Guest presentations by Mr. Marcus Ludwig and Mr. Kai Dührkop.
25.5. Viivi Sahely
1.6. Elena Markus
8.6. Linh Canonical Correlation Analysis based on Hilbert-Schmidt Independence Criterion and Centered Kernel Target Alignment. ICML 2013. Viivi
15.6. Maja Elena
22.6. Parisa Linh
29.6. Eric Maja
6.7. Anna Parisa

Schedule Autumn 2015

Date "Pulla" responsible Journal club paper Lead reader
27.8. Elena Giguere, S, Rolland, A, Laviolette, F, and Marchand, M: Algorithms for the Hard Pre-Image Problem of String Kernels and the General Problem of String Prediction. ICML 2015. Juho
3.9. Celine Elena
10.9. Markus Wang, Q, Zhang, K, Jiang, G and Marsic, I: Improving semi-supervised target alignment via label-aware base kernels. AAAI 2014. Celine
17.9. Jinmin Markus
24.9. A346 Viivi Jinmin
1.10.A346 Jane Sahely
8.10. Su Jane
15.10. Anna Graph regularized non-negative matrix factorisation for data representation TPAMI 2011 by Deng Cai, Xiaofei He, Jiawei Han, Thomas Huang AAAI 2014. Su
22.10. Huibin Preference Completion: Large-scale Collaborative Ranking from Pairwise Comparisons. ICML 2015 Huibin
29.10. Sahely Drug repositioning by integrating target information through a heterogeneous network model. Anna
5.11. Celine Sparse partial least-squares regression and its applications to high-throughput data analysis Viivi
12.11. Elena Celine
19.11. Markus Elena
26.11. Sahely Markus
3.12. Su Sahely
10.12. Sandor Su

Schedule Spring 2015

Date "Pulla" responsible Reading group paper Lead reader
23.1. Sahely Convex Algorithms for Nonnegative Matrix Factorization Viivi
30.1. Elena Large Scale Canonical Correlation Analysis with Iterative Least Squares Sahely
6.2. Jana paper Elena
13.2. Su paper Jana
20.2. Viivi Part and Clamp: Efficient Structured Output Learning Su
27.2. Anna Non-negative Matrix Tri-Factorization for co-clustering: An analysis of the block matrix Viivi
6.3. Huibin Detecting Novel Associations in Large Data Sets Anna
13.3. Jinmin Machine Learning: The High Interest Credit Card of Technical Debt. Software Engineering for Machine Learning (NIPS 2014) Huibin
20.3 Maja paper Jinmin
27.3 no meeting No KEPACoffee meeting due to PhD defense of Hongyu Su
3.4. Easter break no paper
10.4. Iitu paper Maja
17.4. Celine paper Iitu
24.4. Markus A unifying framework for vector-valued manifold regularization and multi-view learning. ICML 2013. Celine
1.5. May Day no meeting
8.5. Sahely paper Markus
15.5. Elena paper Sahely
22.5. Su paper Elena
29.5. Viivi Is Feature Selection Secure against Training Data Poisoning? Su
5.6. Jane Subspace learning for unsupervised feature selection via matrix factorization Viivi
11.6. Huibin paper Jane
18.6. eve of Midsummer eve no meeting
25.6. Anna An embarrassingly simple approach to zero shot learning. (ICML 2015) Huibin
2.7. Iitu paper Anna
9.7. Maja paper Iitu
16.7. Jinmin paper Maja
23.7. Summer break no meeting
30.7. Summer break no meeting

Schedule Autumn 2014

Below is a tentative schedule for the Autumn. Let Juho know if you cannot make it to your own "pulla" or "lead reader" session, or if you cannot make most of the other sessions (it does not matter if you miss one or two), then we will reschedule. All meetings at meeting room A328 at 2.00pm unless otherwise announced.

Date "Pulla" responsible Reading group paper Lead reader
3.9. A346 Celine no paper
10.9. Su High order regularization for semi-supervised learning of structured output problems, ICML 2014 Celine
17.9. Elena Memory Efficient Kernel Approximation. ICML 2014 Su
24.9. Jana Advancing metabolic models with kinetic information by Link et al,Current Opinion in Biotechnology, 29, 2014 Elena
1.10. Viivi paper Jana
8.10. Anna Knowledge-Guided SCCA, Bioinformatics 2014 Viivi
15.10. Huibin paper Anna
22.10. Sahely On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection, ICML 2014 Huibin
29.10. Elena Discrete Chebyshev Classifiers Sahely
5.11 Jana Identification of Metabolic Engineering Targets through Analysis of Optimal and Sub-Optimal Routes PLOS One 2013. Elena
12.11. Celine paper Jana
19.11. Su Simultaneous Twin Kernel Learning using Polynomial Transformations for Structured Prediction, CVPR 2014 Celine
26.11. Huibin Is margin preserved after random projection? ICML 2014 Su
3.12. Anna Fast Prediction for Large-Scale Kernel Machines, NIPS 2014 Huibin
10.12. Viivi paper Anna
17.12. canceled canceled cenceled

Schedule Summer 2014

Below is a tentative schedule for the Summer. Let Juho know if you cannot make \ it to your own "pulla" session, or if you cannot make most of the other session\ s (it does not matter if you miss one or two), then we will reschedule. All meetings at meeting room A328 at 2.30pm unless otherwise announced.
Date "Pulla" responsible Reading group paper
4.6. Juho Kadri et al.:A Generalized Kernel Approach to Structured Output Learning ,ICML 2013
11.6. Elena Integrated Module and Gene-Specific Regulatory Inference Implicates Upstream Signaling Networks, PLOS Computational Biology
19.6. Su Learning structured models with AUC loss and its generalisations AISTATS 2014
25.6. Celine Multi-label Classification via Feature-aware Implicit Label Space Encoding, ICML 2014
2.7. Anna A community effort to assess and improve drug sensitivity prediction algorithms, Nature Biotechnology 2014
9.7. Summer break paper
16.7 Summer break paper
23.7 Summer break paper
30.7 Summer break paper
6.8 Jana paper
13.8 Clemens paper
20.8 Maja Beyond L2-Loss Functions for Learning Sparse Models (Clemens)
27.8 Jinmin (note: Jinmin's presentation is given in the summer intern seminar from 13-14) A Divide-and-Conquer Solver for Kernel Support Vector Machines (Juho)

Schedule Spring 2014

Date "Pulla" responsible Presentation Reading group paper
3.1. Juho Alex Flint Matthew Blascho: "Perceptron Learning of SAT", NIPS 2012
10.1. Jana
17.1. Elena Computational tools for the synthetic design of biochemical pathways. Nature Reviews 2012
24.1. Celine Azencott, C. et al.: "Efficient network-guided multi-locus association mapping with graph cuts", ISMB 2013 and Bioinformatics
31.1. Anna Parallel Random Forest Regression
7.2. Huibin Learning Kernels Using Local Rademacher Complexity. NIPS 2013
14.2. Su Stochastic Gradient Descent. NIPS 2012
21.2 Viivi
28.2 Nicole MetaID: A novel method for identification and quantification of metagenomic samples . BMC
7.3 Clemens Weisfeiler-Lehman Graph Kernels
14.3 Carlos Kernelized Bayesian Matrix Factorization
21.3 Elena Internal coarse-graining of molecular systems. PNAS 2008
28.3 Jana Combining heterogeneous data sources for accurate functional annotation of proteins. BMC Bioinformatics 2013
4.4. Juho Sparse Learning over Infinite Subgraph Features. Arxiv.
11.4. Celine On learning with kernels for unordered pairs. ICML 2010.
16.4. Huibin Kernel-Mapping Recommender system algorithms Information Sciences 2012.
30.4. Anna Prediction of DTI and Drug Repositioning via Network-Based Inference. PLoS Comput Biol 2012
7.5. Su Learning structured models with AUC loss and its generalisations AISTATS 2014
14.5. Clemens - switched with Nicole, was 21.5. -
21.5. Nicole A Statistical Framework for the Functional Analysis of Metagenomes Recomb 2009
28.5. Carlos MEGADOCK 3.0: a high-performance protein-protein interaction prediction software SCFBM 2013

Schedule Autumn 2013

Below is a tentative schedule for the Autumn. Let Juho know if you cannot make it to your own "pulla" session, or if you cannot make most of the other sessions (it does not matter if you miss one or two), then we will reschedule. All meetings at meeting room A328 unless otherwise announced.
Date "Pulla" responsible Presentation
23.8 Juho Xu, Huan, Constantine Caramanis, and Shie Mannor. "Sparse algorithms are not stable: A no-free-lunch theorem." Pattern Analysis and Machine Intelligence, IEEE Transactions on 34, no. 1 (2012): 187-193.
30.8 Jian
6.9 Jana
13.9 Elena
20.9 No meeting (ICS Department get-together)
27.9 No meeting (ICS Recreation Day)
4.10 Jefrey
11.10 Su
18.10 No meeting (ICS Department get-together)
25.10 No meeting (Juho abroad)
1.11 Anna
8.11 Nicole
15.11 No meeting (ICS Department get-together)
22.11 Huibin
29.11 Viivi
6.12 No meeting (Finnish independence day)
13.12 Juho
20.12 No meeting (ICS department get-together)