2006

Paper Title Authors Topic Datasets Relevant
"Introduction to the special issue on multi-relational data mining and statistical relational learning" Hendrik Blockeel, David Jensen, Stefan Kramer No evaluation No
"PRL: A Probabilistic Relational Language" Lise Getoor, John Grant No evaluation No
"Propositionalization-Based Relational Subgroup Discovery with RSD" Filip Železný, Nada Lavrač
  • East-West trains SMALL
  • King-Rook-King SMALL
  • Mutagenesis
  • Telecommunication data NOT AVAILABLE
  • UK Traffic Accidents NOT AVAILABLE
"Distribution-Based Aggregation for Relational Learning with Identifier Attributes" Claudia Perlich, Foster Provost
  • Synthetic telephone fraud
  • BMS-WebView-1
  • Direct marketing (EBooks)
  • Industry classification (COOC)
  • Initial public offerings (IPO)
  • Document classification (CORA)
No
"Markov Logic Networks" Matthew Richardson, Pedro Domingos
  • UW-CSE
No
"XRules: An Effective Algorithm for Structural Classification of XML Data" Mohammed J. Zaki, Charu C. Aggarwal
  • Website log data
  • Synthetic datasets
No
"On Mining Summaries by Objective Measures of Interestingness" Naim Zbidi, Sami Faiz, Mohamed Limam
  • Synthetic data
  • Research awards database (NSERC)
  • Heart disease diagnosis database
  • Hayes Roth database (UCI)
No
"A Unified View on Clustering Binary Data" Tao Li
  • CSTR (abstracts of technical reports)
  • WebKB
  • Reuters-21578
No
"Additive Regularization Trade-Off: Fusion of Training and Validation Levels in Kernel Methods" K. Pelckmans, J. A. K. Suykens, B. De Moor
  • Pima Indians Diabetes Database (UCI)
  • Liver-disorders Database (BUPA, UCI)
No
"Extremely Randomized Trees" Pierre Geurts, Damien Ernst, Louis Wehenkel
  • Waveform
  • Two-Norm
  • Ring-Norm
  • Vehicle
  • Vowel
  • Segment
  • Spambase
  • Satellite
  • Pendigits
  • Dig44
  • Letter
  • Isolet
  • Friedman1
  • Housing
  • Hwang-f5
  • Hwang-f5n
  • Pumadyn-32fh
  • Pumadyn-32nm
  • Abalone
  • Ailerons
  • Elevators
  • Poletelecomm
  • Bank-32nh
  • Census-16H
"Most datasets are available in the UCI Machine Learning Repository"
No
"Data-Guided Model Combination by Decomposition and Aggregation" Mingyang Xu, Michael W. Golay
  • Synthetic data
  • Seismology data
No
"Model-based transductive learning of the kernel matrix" Zhihua Zhang, James T. Kwok, Dit-Yan Yeung
  • Wisconsin breast (UCI)
  • cancer (UCI)
  • ionosphere (UCI)
  • sonar (UCI)
  • wine (UCI)
  • USPS digit recognition
No
"Asymptotic Analysis of Temporal-Difference Learning Algorithms with Constant Step-Sizes" Vladislav B. Tadić No datasets No
"Classification Using Hierarchical Naïve Bayes Models" Helge Langseth, Thomas D. Nielsen
  • postop (UCI)
  • iris (UCI)
  • (UCI)
  • monks-1 (UCI)
  • car (UCI)
  • monks-3 (UCI)
  • glass (UCI)
  • glass2 (UCI)
  • diabetes (UCI)
  • heart (UCI)
  • hepatitis (UCI)
  • pima (UCI)
  • cleve (UCI)
  • wine (UCI)
  • thyroid (UCI)
  • ecoli (UCI)
  • breast (UCI)
  • vote (UCI)
  • crx (UCI)
  • australian (UCI)
  • chess (UCI)
  • vehicle (UCI)
  • soybean-large (UCI)
No
"An Algorithmic Theory of Learning: Robust Concepts and Random Projection" Rosa I. Arriaga, Santosh Vempala No evaluation No
"Classification-Based Objective Functions" Michael Rimer, Tony Martinez
  • ann (UCI)
  • bcw (UCI)
  • ionosphere (UCI)
  • iris (UCI)
  • musk2 (UCI)
  • pima (UCI)
  • sonar (UCI)
  • wine (UCI)
No
"Machine Learning and Games" Michael Bowling, Johannes Fürnkranz, Thore Graepel, Ron Musick No evaluation No
"Adaptive Game AI with Dynamic Scripting" Pieter Spronck, Marc Ponsen, Ida Sprinkhuizen-Kuyper, Eric Postma
  • Synthetic data
No
"Universal Parameter Optimisation in Games Based on SPSA" Levente Kocsis, Csaba Szepesvári
  • Omaha Hi-Lo Poker game
  • McRaise poker game
No
"Learning to Bid in Bridge" Asaf Amit, Shaul Markovitch
  • Bridge game simulation
No
"Learning Long-Term Chess Strategies from Databases" Aleksander Sadikov, Ivan Bratko
  • king and rook versus king endgame
  • king and queen versus king and rook endgame
No

2007

Coming soon...

2008

Coming soon...

2009

Paper Title Authors Topic Datasets Relevant
"Cutting-plane training of structural SVMs" Thorsten Joachims, Thomas Finley, Chun-Nam John Yu A more efficient version of SVMs whose training has a linear complexity w.r.t. the number of instances
  • Covertype dataset of Blackard, Jock & Dean as our benchmark for the multiclass SVM. (7-class problem with n = 522,911 examples and 54 features)
Maybe
"NP-hardness of Euclidean sum-of-squares clustering" Daniel Aloise, Amit Deshpande, Pierre Hansen, Preyas Popat A proof of NP-hardness of Euclidean Distance Clustering No datasets No
"Measuring classifier performance: a coherent alternative to the area under the ROC curve" David J. Hand A new metric which represents an alternative to AUC
  • Thomas et al. (2002): a small data set describing a number of bank customers, along with a good/bad outcome indicator
Maybe
"A theory of learning from different domains" Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman Vaughan A paper concerning the transfer learning problem Sentimental Analysis domain No
"Combining instance-based learning and logistic regression for multilabel classification" Weiwei Cheng, Eyke Hüllermeier A framerwork which unifies instance based methods with logistic regression in the context of multilabel classification
  • Emotions
  • Image
  • Genbase
  • Mediamill
  • Reuters
  • Scene
  • Yeast
No (the ontology would not have enough concepts)
"Graph kernels based on tree patterns for molecules" Pierre Mahé, Jean-Philippe Vert A graph kernel with experiments in the context of toxicity and anti-cancer activity prediction
  • First dataset: (low and high) mutagenic prediction (8 chemical compounds tested for mutagenicity on Salmonella typhimurium)
  • Second dataset: mutagenicity data set was extracted from the carcinogenic potency database (CPDB)
  • Third dataset: NCI anticancer activity dataset. This dataset, made available by the Developmental Therapeutics Program (DTP) of the National Cancer Institute (NCI)
Maybe
"Adaptive regularization of weight vectors" Koby Crammer, Alex Kulezsca, Mark Dredze AROW, a new online learning algorithm that combines several properties of successful : large margin training, confidence weighting, and the capacity to handle non-separable data.
  • Amazon
  • 20 Newsgroups
  • Reuters (RCV1-v2/LYRL2004)
  • Sentiment
  • Spam (from the ECML/PKDD Challenge5)
  • OCRdata
Maybe Amazon and ECML PKDD challenge 5
"Large scale image annotation: learning to rank with joint word-image embeddings" J Weston, S Bengio, N Usunier The authors propose a strongly performing method that scales to such datasets by simultaneously learning to optimize precision at k of the ranked list of annotations for a given image and learning a low-dimensional joint embedding space for both images and annotations.
  • Web-data dataset
  • Image dataset
No
"Cluster-grouping: from subgroup discovery to clustering" Albrecht Zimmermann, Luc De Raedt The problem of cluster-grouping is introduced. It is shown that it can be considered a subtask in several important data mining tasks, such as subgroup discovery, mining correlated patterns, clustering and classification. The algorithm CG for solving cluster-grouping problems is then introduced, and it is incorporated as a component in several existing and novel algorithms for tackling subgroup discovery, clustering and classification
  • Balance-2-Class
  • Breast-W
  • Breast-W-equal
  • Car
  • Colic
  • Colic-equal
  • Credit-G
  • Credit-G-equal
  • Diabetes
  • Diabetes-equal
  • Heart-H
  • Heart-Statlog
  • Heart-Statlog-equal
  • Krkopt
  • Mfeat-Morpho
  • Mfeat-Morpho-equal
  • Nursery
  • Segment
  • Tic-Tac-Toe
  • Voting Record
  • Zoo
  • Pendigits
  • Mushroom
No
"Editorial survey: swarm intelligence for data mining" D Martens, B Baesens, T Fawcett A survey on swarm intelligence for data mining tasks No datasets No
"Concept learning in description logics using refinements operator" Jehns Lehmann, Pascal Hitzler A method based on refinement operators for inducing concept for SW knowledge bases
  • trains
  • moral
  • moral II
  • poker I
  • poker II
  • forte
Likely
"Sparse kernel SVMs via cutting-plane training" T Joachims, CNJ Yu They explore an algorithm for training SVMs with Kernels that can represent the learned rule using arbitrary basis vectors, not just the support vectors (SVs) from the training set. In this way, more flexibility is guaranteed
  • Adult
  • RCV1 CCAT text-classification
  • The MNIST datasets
  • The IJCNN (task 1) dataset
Maybe
"Discretization for naive-Bayes learning: managing discretization bias and variance" Ying Yang, Geoffrey I. Webb A new technique for discretize continue attributes for Naive Bayes
  • LaborNegotiations
  • Annealing
  • Echocardiogram
  • German
  • Iris
  • MultipleFeatures
  • Hepatitis
  • Hypothyroid
  • WineRecognition
  • Satimage
  • Sonar
  • Musk
  • Glass
  • PioneerMobileRobot
  • HeartCleveland
  • HandwrittenDigits
  • LiverDisorders
  • SignLanguage
  • Ionosphere
  • LetterRecognition
  • HorseColic
  • Adult
  • CreditScreening
  • IpumsLa
  • BreastCancer
  • CensusIncome
  • PimaIndiansDiabetes
  • ForestCovertype 581012
  • Vehicle
No
"Efficient covariance matrix update for variable metric evolution strategie" Thorsten Suttorp, Nikolaus Hansen, Christian Igel A technique for improving the efficiency of covariance matrix decomposition No datasets No
"Learning to classify with missing and corrupted features" Ofer Dekel, Ohad Shamir, Lin Xiao Adversarial approach for supervised learning in presence of missing and corrupted feature
  • Breast Cancer Wisconsin
  • The Spambase Dataset
  • USPS dataset
  • MNIST dataset
Maybe Breast Cancer Wisconsin
"gBoost: a mathematical programming approach to graph classification and regression" Hiroto Saigo, Sebastian Nowozin, Tadashi Kadowaki, Taku Kudo, Koji Tsuda In order to avoid frequent pattern enumeration in the context of graph mining, the authors propose a mathematical programming boosting method (gBoost) that progressively collects informative patterns. gBoost extracts classification rules with less iteration than Adaboost Likely
"On the quest for optimal rule learning heuristics" Frederik Janssen, Johannes Fürnkranz The author try at identifying what criteria are responsible for the good performance of a heuristic rule evaluation function in a greedy top-down covering algorithm
  • Anneal
  • Audiology
  • Breast-cancer
  • Cleveland-heart-disease
  • Contact-lenses
  • Credit
  • Glass2
  • Glass
  • Hepatitis
  • Horse-colic
  • Hypothyroid
  • Iris
  • KRKP
  • Labor
  • Lymphography
  • Monk1
  • Monk2
  • Monk3
  • Mushroom
  • Sick-euthyroid
  • Soybean
  • Tic-tac-toe
  • Titanic
  • Vote-1
  • Vote
  • Vowel
  • Wine
  • Auto-mpg
  • Autos
  • Balance-scale
  • Balloons
  • Breast-w
  • Breast-w-d
  • Bridges2
  • Colic
  • Colic.ORIG
  • Credit-a
  • Credit-g
  • Diabetes
  • Echocardiogram
  • Flag
  • Hayes-roth
  • Heart-c
  • Heart-h
  • Heart-statlog
  • House-votes-84
  • Ionosphere
  • Labor-d
  • Lymph
  • Machine
  • Primarytumor
  • Promoters
  • Segment
  • Solar-flare
  • Sonar
  • Vehicle
  • Zoo
Likely
"An efficient algorithm for learning to rank from preference graphs" Tapio Pahikkala, Evgeni Tsivtsivadze, Antti Airola, Jouni Järvinen, Jorma Boberg The authors propose RLS, a kernel-based preference learning algorithm that has computational advantages w.r.t other methods which minimizes function costs as the hinge loss
  • BioInfer corpus
  • Ohsumed
  • Trec2003
  • Trec2004
  • The Jester Joke
No

2010

Paper Title Authors Topic Datasets Relevant
"Semi-supervised local Fisher discriminant analysis for dimensionality reduction" Masashi Sugiyama, Tsuyoshi Idé, Shinichi Nakajima, Jun Sese A semi-supervised dimensionality reduction method which preserves the global structure of unlabeled samples in addition to separating labeled samples in different classes from each other
  • Olivetti face dataset
No
"Sparse canonical correlation analysis" David R. Hardoon, John Shawe-Taylor Sparse CCA. It minimizes the number of feature employed in the primal and dual projection and maximizes the correlation between them
  • The Danish-German corpus from the europal dataset
  • Two paired English-French and English-Spanish
No
"The security of machine learning" Marco Barreno, Blaine Nelson, Anthony D. Joseph, J.D. Tygar A taxonomy of attack against Spam Bayes
  • Text Retrieval Conference (TREC) 2005 spam corpus
No
"Extracting certainty from uncertainty: regret bounded by variation in costs" Elad Hazan, Satyen Kale The authors propose an algorithm for changing the observed costs in the context of prediction from experts No datasets No
"Random classification noise defeats all convex potential boosters" Philip M. Long, Rocco A. Servedio A broad class of boosting algorithms can be interpreted as performing coordinate-wise gradient descent to minimize some potential function of the margins of a data set. The authors proofed that these methods are susceptible to random classification noise Some artificial datasets that are not accessible No
"A multivariate Bayesian scan statistic for early event detection and characterization" Daniel B. Neill, Gregory F. Cooper The authors propose a general framework for event detection in the context of spatial time series data
  • CC (temporal data)
  • AF (temporal data)
  • TH (temporal data)
No
"Time varying undirected graphs" Shuheng Zhou, John Lafferty, Larry Wasserman The authors develop a non-parametric method for estimating time varying graphical structure for multivariate Gaussian distributions using an L1 regularization method No datasets (only simulation) No
"Temporal kernel CCA and its application in multimodal neuronal data analysis" Felix Bießmann, Frank C. Meinecke, Arthur Gretton, Alexander Rauch, Gregor Rainer, Nikos K. Logothetis, Klaus-Robert Müller The authors propose a multivariate extension of CCA for computing a temporal filter. They employ this algorithm for fMRI
  • Own dataset concerning fMRI signals
No
"Multi-domain learning by confidence-weighted parameter combination" Mark Dredze, Alex Kulesza, Koby Crammer The authors propose a multi-domain online learning algorithm based on parameter combination from multiple classifiers.
  • Sentimental analysis domain
  • Spam
No
"Relational retrieval using a combination of path-constrained random walks" Ni Lao, William W. Cohen Scientific literature with rich metadata can be represented as a labeled directed graph. This graph representation enables a number of scientific tasks such as ad-hoc retrieval or named entity recognition (NER) to be formulated as typed proximity queries in the graph. One popular proximity measure is called Random Walk with Restart (RWR)
  • Yeast (obtained from Saccharomyces Genome Database and Gene Ontology)
  • Fly (extracted from Flymine (an integrated database); the rest of the schema is similar to Yeast)
Likely
"On the equivalence of weak learnability and linear separability: new relaxations and efficient boosting algorithms" Shai Shalev-Shwartz, Yoram Singer The authors describe a set of relaxation and propose an efficient framework for boosting algorithm which consider these relaxations No datasets No

2011

Paper Title Authors Topic Datasets Relevant
"Classifier chains for multi-label classification" J Read, B Pfahringer, G Holmes, E Frank A chain classification that improve multilabel classification by considering the correlation between label
  • Music
  • Scene
  • Yeast
  • Genbase
  • Medical
  • Slashdot
  • Enron
  • LangLog
  • Reuters
  • OHSUMED
  • TMC2007
  • IMDB
  • Bibtex
  • MediaMill
  • Delicious
Maybe IMDB, bibtex and Delicious
"Policy Search for Motor Primitives in Robotics" Jens Kober, Jan Peters An EM-inspired algorithm applicable in complex motor learning tasks Some datasets for learning movements in robotics No
"Detecting communities and their evolutions in dynamic social networks—a Bayesian approach" Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, Rong Jin The authors propose a dynamic stochastic block model for finding communities and their evolution in a dynamic social network
  • Generated data
  • DBLP
  • women
Maybe
"Piecewise training for structured prediction,Charles Sutton" Andrew McCallum The authors propose a piece-wise training for structured prediction, where a factors are divided in two sub-graph and trained separately
  • WSJ Penn Treebank data set
  • CoNLL 2003 data set
  • CoNLL 2000 data set
No

2012

Paper Title Authors Topic Datasets Relevant
"Guest Editors' introduction" Frasconi, Lisi No evaluation No
"ILP turns 20" Muggleton, De Raedt, Poole, Bratko, Flach, Inoue, Srinivasan No evaluation No
"Gradient-based boosting for statistical relational learning: The relational dependency network case" Natarajan, Khot, Kersting, Gutmann, Shavlik
  • MLNs
  • UW
  • Movie Lens
  • OMOP simulator data
No
"Bridging logic and kernel machines" Diligenti, Gori, Maggini, Rigutini
  • Synthetic data
  • Tagged BibTex entries FLAT
No
"Applying the information bottleneck to statistical relational learning" Riguzzi, Di Mauro
  • Synthetic data
  • IMDB
  • Cora
No
"Inverse subsumption for complete explanatory induction" Yamamoto, Inoue, Iwanuma No evaluation No
"Data and task parallelism in ILP using MapReduce" Srinivasan, Faruquie, Joshi
  • Synthetic data (trains)
  • NCI-HIV
  • Yeast (KDD Cup 2001)
  • Zinc
  • Mutagenesis
  • Carcinogenesis
  • DSSTox
Likely

2013

Paper Title Authors Topic Datasets Relevant
"Efficiently Learning the Preferences of People" Adriana Birlutiu, Perry Groot, Tom Heskes
  • Letor (documents with relevance levels w.r.t. a certain query) TEXT
  • Audio (sound samples + users' sound quality rating) NUMERIC
  • Art (images + users' ratings) NUMERIC
No
"Density Estimation with Minimization of U-Divergence" Kanta Naito, Shinto Eguchi
  • Synthetic data
No
"New Algorithms for Budget Learning" Kun Deng, Yaling Zheng, Chris Bourke, Stephen Scott, Julie Masciale 'Budget learning': free access to training examples' class labels but 'fee' to pay to access attribute; solution based on algorithms for multi-armed bandit problem
  • Breast-cancer NUMERIC
  • Colic NUMERIC/FLAT
  • Kr-vs-kp FLAT
  • Mushroom FLAT
  • Vote FLAT
  • Zoo FLAT
No
"Learning Figuures with the Hausdorff Metric by Fractals -- Towards computable Binary Classification" Mahito Sugiyama, Eiju Hirowatari, Hideki Tsuiki, Akihiro Yamamoto Numeric data No
"Mass Estimation" Kai Ming Ting, Guang-Tong Zhou, Fei Tony Liu, Swee Chuan Tan
  • Tic FLAT
  • White_wine NUMERIC
  • Quake (earthquake data) NOT FOUND
  • Wine_red NUMERIC
  • Concrete NUMERIC
  • "the eight largest data sets used by Liu et al. (2008)"
    • Http (KDDCUP99) FLAT/NUMERIC
    • ForestCover NUMERIC
    • Mulcross PAPER/DATA NOT AVAILABLE
    • SMTP FLAT/NUMERIC
    • Shuttle FLAT/NUMERIC
    • Mammography DATA NOT AVAILABLE
    • Annthyroid FLAT/NUMERIC
    • Satellite NUMERIC
  • COREL NUMERIC
No
"A Theory of Transfer Learning with Applications to Active Learning" Liu Yang, Steve Hanneke, Jaime Carbonell No datasets No
"Non-homogeneous Dynamic Bayesian Networks with Bayesian Regularization for Inferring Gene Regulartory Networks with Gradually Time-Varying Structure" Frank Dondelinger, Sophie Lèbre, Dirk Husmeier
  • Synthetic data
  • Time series of gene expression data FLAT/NUMERIC
No
"Forecasting Electricity Consumption by Aggregating Specialized Experts" Marie Devaine, Pierre Gaillard, Yannig Goude, Gilles Stoltz
  • Electricity consumption data from Slovakia
  • Electricity consumption data from France
No (NUMERIC)
"Quantum Speed-Up for Unsupervised Learning" Esma Aïmeur, Gilles Brassard, Sébastien Gambs
  • Synthetic data
No
"Online Multiple Kernel Classification" Steven C. H. Hoi, Rong Jin, Peilin Zhao, Tianbao Yang
  • ionosphere
  • votes84
  • wdbc
  • breast
  • australian
  • diabetes
  • fourclass
  • splice
  • dorothea
  • svmguide3
  • svmguide1
  • a3a
  • spambase
  • mushrooms
  • w5a
  • sonar
No
"On Evaluating Stream Learning Algorithms" João Gama, Raquel Sebastião, Pedro Pereira Rodrigues
  • Numeric datasets
No
"Multiclass Classification with Bandit Feedback Using Adaptive Regularization" Koby Crammer, Claudio Gentile
  • 20 newsgroups
  • Amazon7
  • Amazon3
  • Enron A
  • Enron B
  • NYTD
  • NYTO
  • NYTS
  • Reuters
No (TEXT)
"TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots" Todd Hester, Peter Stone
  • Car sensor data
No
"Computational Complexity of Kernel-Based Density-Ratio Estimation: A Condition Number Analysis" Takafumi Kanamori, Taiji Suzuki, Masashi Sugiyama
  • thyroid
  • b-cancer
  • heart
  • german
  • diabetes
  • f-solar
  • image
  • titanic
  • splice
  • waveform
  • banana
  • ringnorm
  • twonorm
No (NUMERIC)
"Exploiting Label Dependencies for Improved Sample Complexity" Lena Chekina, Dan Gutfreund, Aryeh Kontorovich, Lior Rokach, Bracha Shapira
  • Emotions
  • Scene
  • Yeast
  • Genbase
  • Medical
  • Enron
  • Slashdot
  • Ohsumed
  • tmc2007
  • rcv1(subset1)
  • Mediamill
  • Bibtex
No
"Learning with Infinetly Many Features" A. Rakotomamonjy, R. Flamary, F. Yger
  • Synthetic data
  • Adult
  • IJCNN1
No
"Ranking Data with Ordinal Labels: Optimality and Pairwise Aggregation" Stéphan Clémençon, Sylvain Robbiano, Nicolas Vayatis No
"Regularization of Non-Homogeneous Dynamic Bayesian Networks with Global Information-Coupling Based on Hierarchical Bayesian Models" Marco Grzegorczyk, Dirk Husmeier
  • Simulated data from the RAF pathway
  • Synthetic yeast gene network data
  • Gene expression time series
No
"Adaptive Regularization of Weight Vectory" Koby Crammer, Alex Kulesza, Mark Dredze
  • Matrix data
  • Amazon
  • 20 Newsgroups
  • Reuters (RCV1-v2/LYRL2004)
  • Sentiment
  • Spam
  • MNIST
  • USPS
  • Enron
  • NY Times
No
"Semi-Supervised Learning with Density-Ratio Estimation" Masanori Kawakita, Takafumi Kanamori
  • banana
  • breast-cancer
  • diabetis
  • diabetis
  • flare-solar
  • flare-solar
  • german
  • heart
  • image
  • ringnorm
  • splice
  • thyroid
  • thyroid
  • titanic
  • twonorm
  • waveform
No
"Sparse Non Gaussian Component Analysis by Semidefinite Programming" Elmar Diederichs, Anatoli Juditsky, Arkadi Nemirovski, Vladimir Spokoiny
  • Numeric datasets
No
"Completing Causal Networks by Meta-Level Abduction" Katsumi Inoue, Andrei Doncescu, Hidetomo Nabeshima
  • Synthetic networks
No
"Learning a Factor Model via Regularized PCA" Yi-Hao Kao, Benjamin Van Roy
  • Synthetic data
  • Historical prices of stocks
No
"Alignment Based Kernel Learning with a Continuous Set of Base Kernels" Arash Afkanpour, Csaba Szepesvári, Michael Bowling
  • Synthetic data
  • MNIST
  • UCI letter recognition
  • Delve datasets
    • Banana
    • Breast Cancer
    • Diabetes
    • German
    • Heart
    • Image Seg.
    • Ringnorm
    • Sonar
    • Splice
    • Thyroid
    • Waveform
No
"Minimax PAC Bounds on the Sample Complexity of Reinforcement Learning with a Generative Model" Mohammad Gheshlaghi Azar, Rémi Munos, Hilbert J. Kappen No datasets No
"Guest editors’ introduction: special issue of selected papers from ECML-PKDD 2012" Tijl De Bie, Peter A. Flach No evaluation No
"A Reinforcement Learning Approach to Autonomous Decision-Making in Smart Electricity Markets" Markus Peters, Wolfgang Ketter, Maytal Saar-Tsechansky, John Collins
  • Simulated data
No
"Active Evaluation of Ranking Functions Based on Graded Relevance" Christoph Sawade, Steffen Bickel, Timo von Oertzen, Tobias Scheffer, Niels Landwehr
  • MSLR-WEB30k
No
"Beam Search Algorithms for Multilabel Learning" Abhishek Kumar, Shankar Vembu, Aditya Krishna Menon, Charles Elkan
  • Emotions
  • Scene
  • Yeast
  • Genbase
  • Medical
  • Enron
No
"Exploiting Symmetries for Scaling Loopy Belief Propagation and Relational Training" Babak Ahmadi, Kristian Kersting, Martin Mladenov, Sriraam Natarajan
  • Friends-and-smokers dataset + own extensions
  • Voting MLN from the Alchemy repository
  • Cora entity resolution MLN from Alchemy repository
  • Simple version of the Wumpus task (Russell and Norvig 2003)
No
"Geometry Preserving Multi-Task Metric Learning" Peipei Yang, Kaizhu Huang, Cheng-Lin Liu No
"Learning Policies for Battery Usage Optimization in Electric Vehicles" Stefano Ermon, Yexiang Xue, Carla Gomes, Bart Selman
  • Trips data
No
"Massively Parallel Feature Selection: An Approach Based on Variance Preservation" Zheng Zhao, Ruiwen Zhang, James Cox, David Duling, Warren Sarle No
"Introduction: special issue of selected papers of ACML 2012" Zhi-Hua Zhou, Wee Sun Lee, Steven C.H. Hoi, Wray Buntine, Hiroshi Motoda No evaluation No
"Bayesian Object Matching" Arto Klami
  • Artificial data
  • Image data
  • Time series of concentrations of metabolites
  • More than 300 documents extracted from the Europarl corpus and represented as TF-IDF vectors
No
"Recovering Networks from Distance Data" Sandhya Prabhakaran, David Adametz, Karin J. Metzner, Alexander Böhm, Volker Roth
  • Synthetic data
  • Dataset of promoter activity data from Escherichia coli operons (Zaslaver et al. 2006)
No
"Correlated Topographic Analysis: Estimating am Odering of Correlated Components" Hiroaki Sasaki, Michael U. Gutmann, Hayaru Shouno, Aapo Hyvärinen
  • natural images
  • outputs of simulated complex cells
  • text data
No
"Variational Bayeasian Sparse Additive Matrix Factorization" Shinichi Nakajima, Masashi Sugiyama, S. Derin Babacan
  • Different video datasets
No
"Conditional Validity of Inductive Conformal Predictors" Vladimir Vovk
  • Spambase
No
"Exploration and Exploitation of Scratch Games" Raphaël Féraud, Tanguy Urvoy Scratch game = "variant of the multi-armed bandit model"
  • Synthetic data
  • Ad server optimization data
No
"Hypervolume Indicator and Dominance Reward Based Multi-Objective Monte-Carlo Tree Search" Weijia Wang, Michèle Sebag
  • The Deep Sea Treasure (DST) problem
  • Resource gathering task
  • Grid scheduling
No
"Modeling Individual Email Patterns Over Time with Latent Variable Models" Nicholas Navaroli, Christopher DuBois, Padhraic Smyth
  • E-mail text data
No
"On Using Nearly-Independent Feature Families for High Precision and Confidence" Omid Madani, Manfred Georg, David Ross
  • Video and text classification
No
"Multi-Stage Classifier Design" Kirill Trapeznikov, Venkatesh Saligrama, David Castañón No
"Guest Editor's Introduction: Special Issue of the ECML PKDD 2013 Journal Track" Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Železný No evaluation No
"Probabilistic Topic Models for Sequence Data" Nicola Barbieri, Giuseppe Manco, Ettore Ritacco, Marco Carnuccio, Antonio Bevacqua
  • Text data
No
"Block Coordinate Descent Algorithms for Large-Scale Sparse Multiclass Classification" Mathieu Blondel, Kazuhiro Seki, Kuniaki Uehara
  • Amazon7 (product-review classificatio)
  • RCV1 (news document classification)
  • MNIST (handwritten digit classification)
  • News20 (newgroup message classification)
  • Sector (web-page-industry sectors classification)
No
"The Flip-the-State Transition Operator for Restricted Boltzmann Machines" Kai Brügge, Asja Fischer, Christian Igel
  • 'Bars and Stripes' data
  • MNIST data
No
"ROC Curves in Cost Space" José Hernández-Orallo, Peter Flach, César Ferri
  • German credit data
No
"A Comparative Evaluation of Stochastic-Based Interface Methods for Gaussian Process Models" M. Filippone, M. Zhong, M. Girolami
  • Synthetic data
  • Pima (UCI)
  • Wisconsin (UCI)
  • SPECT (UCI)
  • Ionosphere (UCI)
No
"Spatio-temporal Random Fields: Compressible Representation and Distributed Estimation" Nico Piatkowski, Sangkyun Lee, Katharina Morik
  • Sensor reading datasets (traffic, temperature)
No
"Pairwise Meta-Rules for Better Meta-Learning-Based Algorithm Ranking " Quan Sun, Bernhard Pfahringer 466 datasets: "we chose to use as many datasets as possible from various public data sources, including the UCI, StatLib, KDD and WEKA repositories" (actual datasets not named) No
"Differential Privacy Based on Importance Weighting" Zhanglong Ji, Charles Elkan
  • Dataset derived from Adult (UCI)
No
"Editorial: Preference Learning and Ranking" Eyke Hüllermeier, Johannes Fürnkranz No evaluation No
"Supervised Clustering of Label Ranking Data Using Label Preference Information" Mihajlo Grbovic, Nemanja Djuric, Shengbo Guo, Slobodan Vucetic
  • Datasets derived from UCI and Statlog datasets (not available)
  • Sushi preference data
  • Yeast genome profile data
  • Five different microarray datasets
No
"Calibration and Regret Bounds for Order-Preserving Surrogate Losses in Learning to Rank" Clément Calauzènes, Nicolas Usunier, Patrick Gallinari No datasets No
"Tune and Mix: Learning to Rank Using Ensembles of Calibrated Multi-Class Classifiers" Róbert Busa-Fekete, Balázs Kégl, Tamás Éltető, György Szarvas
  • OHSUMED
  • MQ2007
  • MQ2008
  • YAHOO1
  • YAHOO2
  • MS1
  • MS2
No
"BoostingTree: Parallel Selection of Weak Learners in Boosting, with Application to Ranking" Levente Kocsis, András György, Andrea N. Bán No
"Efficient Regularized Least-Squares Algorithms for Conditional Rankning on Relational Data" Tapio Pahikkala, Antti Airola, Michiel Stock, Bernard De Baets, Willem Waegeman
  • Synthetic data
  • 20-newsgroups
  • Bacterial data
No
"Sequential Event Prediction" Benjamin Letham, Cynthia Rudin, David Madigan
  • email recipient recommendation
  • patient condition prediction
  • online grocery store recommender system
No
"Robust Ordinal Regression in Preference Learning and Ranking" Salvatore Corrente, Salvatore Greco, Miłosz Kadziński, Roman Słowiński
  • "data set published by the Economist Intelligence Unit (EIU) in 2007"
No

2014

Coming soon...

2015

Coming soon...