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Juho Rousu
Person information
- affiliation: Aalto University, Espoo, Finland
- affiliation (former): University of Helsinki, Finland
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2020 – today
- 2024
- [j40]Robert Ebo Armah-Sekum, Sándor Szedmák
, Juho Rousu:
Protein function prediction through multi-view multi-label latent tensor reconstruction. BMC Bioinform. 25(1): 174 (2024) - [j39]Maryam Astero
, Juho Rousu:
Learning symmetry-aware atom mapping in chemical reactions through deep graph matching. J. Cheminformatics 16(1): 46 (2024) - [j38]Sándor Szedmák
, Riikka Huusari
, Tat Hong Duong Le, Juho Rousu:
Scalable variable selection for two-view learning tasks with projection operators. Mach. Learn. 113(6): 3525-3544 (2024) - [i12]Fatemeh Abbasi, Juho Rousu:
New methods for drug synergy prediction: a mini-review. CoRR abs/2404.02484 (2024) - 2023
- [i11]Sándor Szedmák, Riikka Huusari, Tat Hong Duong Le, Juho Rousu:
Scalable variable selection for two-view learning tasks with projection operators. CoRR abs/2307.01558 (2023) - 2022
- [j37]Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Vector-Valued Least-Squares Regression under Output Regularity Assumptions. J. Mach. Learn. Res. 23: 344:1-344:50 (2022) - [j36]Eric Bach
, Emma Schymanski
, Juho Rousu
:
Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data. Nat. Mac. Intell. 4(12): 1224-1237 (2022) - [j35]Maryam Sabzevari
, Sándor Szedmák
, Merja Penttilä
, Paula Jouhten
, Juho Rousu
:
Strain design optimization using reinforcement learning. PLoS Comput. Biol. 18(6) (2022) - [c40]Luc Brogat-Motte, Rémi Flamary, Céline Brouard
, Juho Rousu, Florence d'Alché-Buc:
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. ICML 2022: 2321-2335 - [i10]Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. CoRR abs/2202.03813 (2022) - [i9]Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Vector-Valued Least-Squares Regression under Output Regularity Assumptions. CoRR abs/2211.08958 (2022) - 2021
- [j34]Eric Bach
, Simon Rogers
, John Williamson, Juho Rousu:
Probabilistic framework for integration of mass spectrum and retention time information in small molecule identification. Bioinform. 37(12): 1724-1731 (2021) - [j33]Tianduanyi Wang, Sándor Szedmák
, Haishan Wang, Tero Aittokallio
, Tapio Pahikkala
, Anna Cichonska
, Juho Rousu:
Modeling drug combination effects via latent tensor reconstruction. Bioinform. 37(Supplement): 93-101 (2021) - [j32]Grímur Hjörleifsson Eldjárn
, Andrew Ramsay, Justin J. J. van der Hooft
, Katherine R. Duncan
, Sylvia Soldatou
, Juho Rousu
, Rónán Daly
, Joe Wandy
, Simon Rogers:
Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions. PLoS Comput. Biol. 17(5) (2021) - [i8]Riikka Huusari, Sahely Bhadra, Cécile Capponi, Hachem Kadri, Juho Rousu:
Learning primal-dual sparse kernel machines. CoRR abs/2108.12199 (2021) - 2020
- [i7]Sándor Szedmák, Anna Cichonska, Heli Julkunen, Tapio Pahikkala, Juho Rousu:
A Solution for Large Scale Nonlinear Regression with High Rank and Degree at Constant Memory Complexity via Latent Tensor Reconstruction. CoRR abs/2005.01538 (2020) - [i6]Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Learning Output Embeddings in Structured Prediction. CoRR abs/2007.14703 (2020)
2010 – 2019
- 2019
- [j31]Markus Heinonen, Maria Osmala
, Henrik Mannerström
, Janne Wallenius
, Samuel Kaski, Juho Rousu, Harri Lähdesmäki:
Bayesian metabolic flux analysis reveals intracellular flux couplings. Bioinform. 35(14): i548-i557 (2019) - [c39]Viivi Uurtio, Sahely Bhadra, Juho Rousu:
Large-Scale Sparse Kernel Canonical Correlation Analysis. ICML 2019: 6383-6391 - 2018
- [j30]Anna Cichonska
, Tapio Pahikkala
, Sándor Szedmák
, Heli Julkunen, Antti Airola
, Markus Heinonen, Tero Aittokallio
, Juho Rousu:
Learning with multiple pairwise kernels for drug bioactivity prediction. Bioinform. 34(13): i509-i518 (2018) - [j29]Sahely Bhadra
, Peter Blomberg, Sandra Castillo
, Juho Rousu:
Principal metabolic flux mode analysis. Bioinform. 34(14): 2409-2417 (2018) - [j28]Eric Bach
, Sándor Szedmák
, Céline Brouard
, Sebastian Böcker
, Juho Rousu:
Liquid-chromatography retention order prediction for metabolite identification. Bioinform. 34(17): i875-i883 (2018) - [j27]Viivi Uurtio
, João M. Monteiro, Jaz S. Kandola, John Shawe-Taylor
, Delmiro Fernandez-Reyes, Juho Rousu
:
A Tutorial on Canonical Correlation Methods. ACM Comput. Surv. 50(6): 95:1-95:33 (2018) - [c38]Viivi Uurtio, Sahely Bhadra, Juho Rousu:
Sparse Non-linear CCA through Hilbert-Schmidt Independence Criterion. ICDM 2018: 1278-1283 - [i5]Markus Heinonen, Maria Osmala, Henrik Mannerström, Janne Wallenius, Samuel Kaski, Juho Rousu, Harri Lähdesmäki:
Bayesian Metabolic Flux Analysis reveals intracellular flux couplings. CoRR abs/1804.06673 (2018) - 2017
- [j26]Emma Schymanski
, Christoph Ruttkies, Martin Krauss
, Céline Brouard
, Tobias Kind
, Kai Dührkop
, Felicity Allen, Arpana Vaniya, Dries Verdegem, Sebastian Böcker
, Juho Rousu, Huibin Shen, Hiroshi Tsugawa, Tanvir Sajed, Oliver Fiehn, Bart Ghesquière
, Steffen Neumann:
Critical Assessment of Small Molecule Identification 2016: automated methods. J. Cheminformatics 9(1): 22:1-22:21 (2017) - [j25]Sahely Bhadra
, Samuel Kaski
, Juho Rousu
:
Multi-view kernel completion. Mach. Learn. 106(5): 713-739 (2017) - [j24]Anna Cichonska
, Balaguru Ravikumar
, Elina Parri
, Sanna Timonen
, Tapio Pahikkala
, Antti Airola
, Krister Wennerberg
, Juho Rousu
, Tero Aittokallio
:
Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors. PLoS Comput. Biol. 13(8) (2017) - [c37]Céline Brouard, Eric Bach, Sebastian Böcker
, Juho Rousu:
Magnitude-Preserving Ranking for Structured Outputs. ACML 2017: 407-422 - [i4]Viivi Uurtio, João M. Monteiro, Jaz S. Kandola, John Shawe-Taylor, Delmiro Fernandez-Reyes, Juho Rousu:
A Tutorial on Canonical Correlation Methods. CoRR abs/1711.02391 (2017) - 2016
- [j23]Céline Brouard
, Huibin Shen, Kai Dührkop
, Florence d'Alché-Buc
, Sebastian Böcker
, Juho Rousu:
Fast metabolite identification with Input Output Kernel Regression. Bioinform. 32(12): 28-36 (2016) - [j22]Anna Cichonska
, Juho Rousu, Pekka Marttinen
, Antti J. Kangas
, Pasi Soininen, Terho Lehtimäki
, Olli T. Raitakari, Marjo-Riitta Järvelin, Veikko Salomaa, Mika Ala-Korpela
, Samuli Ripatti, Matti Pirinen
:
metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis. Bioinform. 32(13): 1981-1989 (2016) - [j21]Aalt D. J. van Dijk, Harri Lähdesmäki, Dick de Ridder, Juho Rousu:
Selected proceedings of Machine Learning in Systems Biology: MLSB 2016. BMC Bioinform. 17(S-16): 51-52 (2016) - [c36]Markus Heinonen, Henrik Mannerström, Juho Rousu, Samuel Kaski, Harri Lähdesmäki:
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo. AISTATS 2016: 732-740 - [c35]Huibin Shen, Sándor Szedmák, Céline Brouard
, Juho Rousu:
Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning. DS 2016: 427-441 - [i3]Sahely Bhadra, Samuel Kaski, Juho Rousu:
Multi-view Kernel Completion. CoRR abs/1602.02518 (2016) - 2015
- [j20]Hongyu Su, Juho Rousu:
Multilabel classification through random graph ensembles. Mach. Learn. 99(2): 231-256 (2015) - [c34]Viivi Uurtio, Malin Bomberg, Kristian Nybo, Merja Itävaara
, Juho Rousu:
Canonical Correlation Methods for Exploring Microbe-Environment Interactions in Deep Subsurface. Discovery Science 2015: 299-307 - [i2]Sebastian Böcker
, Juho Rousu, Emma Schymanski
:
Computational Metabolomics (Dagstuhl Seminar 15492). Dagstuhl Reports 5(11): 180-192 (2015) - 2014
- [j19]Huibin Shen, Kai Dührkop
, Sebastian Böcker
, Juho Rousu:
Metabolite identification through multiple kernel learning on fragmentation trees. Bioinform. 30(12): 157-164 (2014) - [j18]Esa Pitkänen
, Paula Jouhten
, Jian Hou, Muhammad Fahad Syed, Peter Blomberg, Jana Kludas, Merja Oja, Liisa Holm
, Merja Penttilä
, Juho Rousu, Mikko Arvas
:
Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species. PLoS Comput. Biol. 10(2) (2014) - [c33]Hongyu Su, Aristides Gionis, Juho Rousu:
Structured Prediction of Network Response. ICML 2014: 442-450 - [c32]Mario Marchand, Hongyu Su, Emilie Morvant, Juho Rousu, John Shawe-Taylor:
Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks. NIPS 2014: 873-881 - 2013
- [j17]Juho Rousu, Daniel D. Agranoff, Olugbemiro Sodeinde, John Shawe-Taylor
, Delmiro Fernandez-Reyes
:
Biomarker Discovery by Sparse Canonical Correlation Analysis of Complex Clinical Phenotypes of Tuberculosis and Malaria. PLoS Comput. Biol. 9(4) (2013) - [c31]Hongyu Su, Juho Rousu:
Multilabel Classification through Random Graph Ensembles. ACML 2013: 404-418 - [i1]Hongyu Su, Juho Rousu:
Multilabel Classification throughout Random Graph Ensembles. CoRR abs/1310.8428 (2013) - 2012
- [j16]Markus Heinonen, Huibin Shen, Nicola Zamboni
, Juho Rousu:
Metabolite identification and molecular fingerprint prediction through machine learning. Bioinform. 28(18): 2333-2341 (2012) - [c30]Markus Heinonen, Niko Välimäki, Veli Mäkinen, Juho Rousu:
Efficient Path Kernels for Reaction Function Prediction. BIOINFORMATICS 2012: 202-207 - 2011
- [j15]Markus Heinonen, Sampsa Lappalainen, Taneli Mielikäinen, Juho Rousu:
Computing Atom Mappings for Biochemical Reactions without Subgraph Isomorphism. J. Comput. Biol. 18(1): 43-58 (2011) - [c29]Esa Pitkänen, Juho Rousu, Mikko Arvas:
Minimum Mutation Algorithm for Gapless Metabolic Network Evolution. BIOINFORMATICS 2011: 28-38 - [c28]Esa Pitkänen, Mikko Arvas, Juho Rousu:
Reconstructing Gapless Ancestral Metabolic Networks. BIOSTEC (Selected Papers) 2011: 126-140 - [c27]Hongyu Su, Juho Rousu:
Multi-task Drug Bioactivity Classification with Graph Labeling Ensembles. PRIB 2011: 157-167 - 2010
- [c26]Katja Astikainen, Esa Pitkänen, Juho Rousu, Liisa Holm, Sándor Szedmák:
Reaction Kernels - Structured Output Prediction Approaches for Novel Enzyme Function. BIOINFORMATICS 2010: 48-55 - [c25]Katja Astikainen, Liisa Holm
, Esa Pitkänen
, Sándor Szedmák, Juho Rousu:
Structured Output Prediction of Novel Enzyme Function with Reaction Kernels. BIOSTEC (Selected Papers) 2010: 367-379 - [c24]Hongyu Su, Markus Heinonen, Juho Rousu:
Structured Output Prediction of Anti-cancer Drug Activity. PRIB 2010: 38-49 - [c23]Saso Dzeroski, Pierre Geurts, Juho Rousu:
Preface. MLSB 2010: 1-2 - [e1]Saso Dzeroski, Pierre Geurts, Juho Rousu:
Proceedings of the third International Workshop on Machine Learning in Systems Biology, MLSB 2009, Ljubljana, Slovenia, September 5-6, 2009. JMLR Proceedings 8, JMLR.org 2010 [contents]
2000 – 2009
- 2009
- [j14]Esa Pitkänen
, Paula Jouhten
, Juho Rousu:
Inferring branching pathways in genome-scale metabolic networks. BMC Syst. Biol. 3: 103 (2009) - 2008
- [j13]Ari Rantanen, Juho Rousu, Paula Jouhten
, Nicola Zamboni
, Hannu Maaheimo, Esko Ukkonen
:
An analytic and systematic framework for estimating metabolic flux ratios from 13C tracer experiments. BMC Bioinform. 9 (2008) - [c22]Esa Pitkänen, Ari Rantanen, Juho Rousu, Esko Ukkonen:
A Computational Method for Reconstructing Gapless Metabolic Networks. BIRD 2008: 288-302 - 2007
- [j12]Samuel Kaski, Juho Rousu, Esko Ukkonen
:
Probabilistic modeling and machine learning in structural and systems biology. BMC Bioinform. 8(S-2) (2007) - [j11]Jorma Rissanen, Peter D. Grünwald, Jukka Heikkonen, Petri Myllymäki
, Teemu Roos
, Juho Rousu:
Information Theoretic Methods for Bioinformatics. EURASIP J. Bioinform. Syst. Biol. 2007 (2007) - 2006
- [j10]Ari Rantanen, Taneli Mielikäinen, Juho Rousu, Hannu Maaheimo, Esko Ukkonen
:
Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes. Bioinform. 22(10): 1198-1206 (2006) - [j9]Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor:
Kernel-Based Learning of Hierarchical Multilabel Classification Models. J. Mach. Learn. Res. 7: 1601-1626 (2006) - [j8]Ari Rantanen, Hannu Maaheimo, Esa Pitkänen, Juho Rousu, Esko Ukkonen:
Equivalence of Metabolite Fragments and Flow Analysis of Isotopomer Distributions for Flux Estimation. Trans. Comp. Sys. Biology 6: 198-220 (2006) - [c21]Markus Heinonen, Ari Rantanen, Taneli Mielikäinen, Esa Pitkänen, Juha Kokkonen, Juho Rousu:
Ab Initio Prediction of Molecular Fragments from Tandem Mass Spectrometry Data. German Conference on Bioinformatics 2006: 40-53 - [c20]Tapio Elomaa, Jussi Kujala, Juho Rousu:
Practical Approximation of Optimal Multivariate Discretization. ISMIS 2006: 612-621 - 2005
- [j7]Juho Rousu, John Shawe-Taylor:
Efficient Computation of Gapped Substring Kernels on Large Alphabets. J. Mach. Learn. Res. 6: 1323-1344 (2005) - [c19]Tapio Elomaa
, Jussi Kujala, Juho Rousu:
Approximation Algorithms for Minimizing Empirical Error by Axis-Parallel Hyperplanes. ECML 2005: 547-555 - [c18]Ari Rantanen, Taneli Mielikäinen, Juho Rousu, Esko Ukkonen:
Planning isotopomer measurements for estimation of metabolic fluxes. German Conference on Bioinformatics 2005: 177-191 - [c17]Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor
:
Learning hierarchical multi-category text classification models. ICML 2005: 744-751 - [c16]Esa Pitkänen, Ari Rantanen, Juho Rousu, Esko Ukkonen
:
Finding Feasible Pathways in Metabolic Networks. Panhellenic Conference on Informatics 2005: 123-133 - 2004
- [j6]Tapio Elomaa
, Juho Rousu:
Efficient Multisplitting Revisited: Optima-Preserving Elimination of Partition Candidates. Data Min. Knowl. Discov. 8(2): 97-126 (2004) - 2003
- [j5]Tapio Elomaa, Juho Rousu:
Necessary and Sufficient Pre-processing in Numerical Range Discretization. Knowl. Inf. Syst. 5(2): 162-182 (2003) - [c15]Juho Rousu, Ari Rantanen, Hannu Maaheimo, Esa Pitkänen
, Katja Saarela, Esko Ukkonen
:
A Method for Estimating Metabolic Fluxes from Incomplete Isotopomer Information. CMSB 2003: 88-103 - [c14]Tapio Elomaa, Juho Rousu:
On Decision Boundaries of Naïve Bayes in Continuous Domains. PKDD 2003: 144-155 - 2002
- [j4]Tapio Elomaa
, Juho Rousu:
Linear-Time Preprocessing in Optimal Numerical Range Partitioning. J. Intell. Inf. Syst. 18(1): 55-70 (2002) - [c13]Tapio Elomaa, Juho Rousu:
Fast Minimum Training Error Discretization. ICML 2002: 131-138 - 2001
- [j3]Tapio Elomaa, Juho Rousu:
On the Computational Complexity of Optimal Multisplitting. Fundam. Informaticae 47(1-2): 35-52 (2001) - [j2]Juho Rousu, Robert J. Aarts:
An integrated approach to bioprocess recipe design. Integr. Comput. Aided Eng. 8(4): 363-373 (2001) - [c12]Tapio Elomaa, Juho Rousu:
Preprocessing Opportunities in Optimal Numerical Range Partitioning. ICDM 2001: 115-122 - 2000
- [c11]Tapio Elomaa, Juho Rousu:
Generalizing Boundary Points. AAAI/IAAI 2000: 570-576 - [c10]Tapio Elomaa, Juho Rousu:
On the Complexity of Optimal Multisplitting. ISMIS 2000: 552-561
1990 – 1999
- 1999
- [j1]Tapio Elomaa
, Juho Rousu:
General and Efficient Multisplitting of Numerical Attributes. Mach. Learn. 36(3): 201-244 (1999) - [c9]Juho Rousu, Tapio Elomaa, Robert J. Aarts:
Predicting the Speed of Beer Fermentation in Laboratory and Industrial Scale. IWANN (2) 1999: 893-901 - [c8]Tapio Elomaa, Juho Rousu:
Speeding Up the Search for Optimal Partitions. PKDD 1999: 89-97 - 1998
- [c7]Tapio Elomaa, Juho Rousu:
Postponing the Evaluation of Attributes with a High Number of Boundary Points. PKDD 1998: 221-229 - 1997
- [c6]Robert J. Aarts, Juho Rousu:
Qualitative Knowledge to Support Reasoning About Cases. ICCBR 1997: 489-498 - [c5]Tapio Elomaa, Juho Rousu:
Well-Behaved Evaluation Functions for Numerical Attributes. ISMIS 1997: 147-156 - [c4]Tapio Elomaa, Juho Rousu:
Efficient Multisplitting on Numerical Data. PKDD 1997: 178-188 - [c3]Tapio Elomaa, Juho Rousu:
On the Well-Behavedness of Important Attribute Evaluation Functions. SCAI 1997: 95-106 - 1996
- [c2]Robert J. Aarts, Juho Rousu:
Towards CBR for Bioprocess Planning. EWCBR 1996: 16-27 - [c1]Juho Rousu, Robert J. Aarts:
Adaptation Cost as a Criterion for Solution Evaluation. EWCBR 1996: 354-361
Coauthor Index
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