See below for the main-track parallel sessions on Tuesday, Wednesday, and Thursday. The journal track papers (marked with*) have 25 minutes, the regular papers have 20 minutes, both including discussion.

Tuesday 24th September

Tue1A: Reinforcement Learning

Chair: Pascal Poupart
11:00 – 12:20

Learning graph-based representations for continuous reinforcement learning domains
Jan Hendrik Metzen
(poster stand #1)
Greedy confidence pursuit: A pragmatic approach to multi-bandit optimization
Philip Bachman and Doina Precup
(poster stand #2)
Exploiting multi-step sample trajectories for approximate value iteration
Robert Wright, Lei Yu, Steven Loscalzo, and Philip Dexter
(poster stand #3)
Automatically mapped transfer between reinforcement learning tasks via three-way restricted Boltzmann machines
Haitham Bou Ammar, Decebal Constantin Mocanu, Matthew Taylor, Kurt Driessens, Gerhard Weiss, and Karl Tuyls
(poster stand #4)

Tue1B: Networks (1)

Chair: Francesco Bonchi
11:00 – 12:25

What Distinguish One from Its Peers in Social Networks?*
Yi-Chen Lo, Jhao-Yin Li, Mi-Yen Yeh, Shou-De Lin, and Jian Pei
(poster stand #5) Implementation
Detecting bicliques in GF[q]
Jan Ramon, Pauli Miettinen, and Jilles Vreeken
(poster stand #6)
As Strong as the Weakest Link: Mining Diverse Cliques in Weighted Graphs
Petko Bogdanov, Ben Baumer, Prithwish Basu, Amotz Bar-Noy, and Ambuj Singh
(poster stand #7)
How robust is the core of a network?
Abhijin Adiga and Anil Vullikanti
(poster stand #8)

Tue1C: Privacy and Security

Chair: Stan Matwin
11:00 – 12:25

Differential Privacy Based on Importance Weighting*
Zhanglong Ji and Charles Elkan
(poster stand #9)
Anonymizing data with relational and transaction attributes
Giorgos Poulis, Grigorios Loukides, Aris Gkoulalas-Divanis, and Spiros Skiadopoulos
(poster stand #10)
Privacy-preserving mobility monitoring using sketches of stationary sensor readings
Michael Kamp, Christine Kopp, Michael Mock, Mario Boley, and Michael May
(poster stand #11)
Evasion attacks against machine learning at test time
Battista Biggio, Igino Corona, Davide Maiorca, Blaine Nelson, Nedim Srndic, Pavel Laskov, Giorgio Giacinto, and Fabio Roli
(poster stand #12) Implementation

Tue1D: Ranking and Recommender Systems

Chair: Katharina Morik
11:00 – 12:25

Growing a List*
Benjamin Letham, Cynthia Rudin, and Katherine A Heller
(poster stand #13)
A pairwise label ranking method with imprecise scores and partial predictions
Sebastien Destercke
(poster stand #14)
Learning Socially Optimal Information Systems from Egoistic Users
Karthik Raman and Thorsten Joachims
(poster stand #15)
Socially Enabled Preference Learning from Implicit feedback data
Julien Delporte, Alexandros Karatzoglou, Tomasz Matuszczyk, and Stephane Canu
(poster stand #16)

Tue2A: Markov Decision Processes

Chair: Franz Pernkopf
14:15 – 15:55

Expectation maximization for average reward decentralized POMDPs
Joni Pajarinen and Jaakko Peltonen
(poster stand #17) Implementation
Properly acting under partial observability with action feasibility constraints
Caroline Carvalho Chanel and Florent Teichteil-Konigsbuch
(poster stand #18)
Iterative model refinement of recommender MDPs based on expert feedback
Omar Khan, Pascal Poupart, and John Mark Agosta
(poster stand #19)
Solving relational MDPs with exogenous events and additive rewards
Saket Joshi, Roni Khardon, Prasad Tadepalli, Aswin Raghavan, and Alan Fern
(poster stand #20)
Continuous upper confidence trees with polynomial exploration-consistency
Adrien Couetoux, David Auger, and Olivier Teytaud
(poster stand #21)

Tue2B: Tensor Analysis & Dimensionality Reduction

Chair: Charles Elkan
14:15 – 15:55

An analysis of tensor models for learning on structured data
Maximilian Nickel and Volker Tresp
(poster stand #22)
Learning modewise independent components from tensor data using multilinear mixing model
Haiping Lu
(poster stand #23)
Embedding with Autoencoder Regularization
Wenchao Yu, Guangxiang Zeng, Ping Luo, Fuzhen Zhuang, Qing He, and Zhongzhi Shi
(poster stand #24)
Learning Exemplar-Represented Manifolds in Latent Space for Classification
Shu Kong and Donghui Wang
(poster stand #25)
Locally Linear Landmarks for Large-Scale Manifold Learning
Max Vladymyrov and Miguel Carreira-Perpinan
(poster stand #26) Implementation

Tue2C: Biomedical Applications

Chair: Jesse Davis
14:15 – 15:55

Forest-Based Point Process for Event Prediction from Electronic Health Records
Jeremy Weiss, Michael Caldwell, and David Page
(poster stand #27)
On Discovering the Correlated Relationship between Static and Dynamic Data in Clinical Gait Analysis
Yin Song, Jian Zhang, Longbing Cao, and Morgan Sangeux
(poster stand #28)
Computational Drug Repositioning by Ranking and Integrating Multiple Data Sources
Ping Zhang, Pankaj Agarwal, and Zoran Obradovic
(poster stand #29)
Score As You Lift (SAYL): A Statistical Relational Learning Approach to Uplift Modeling
Houssam Nassif, Finn Kuusisto, Elizabeth Burnside, David Page, Jude Shavlik, and Vitor Santos Costa
(poster stand #30)
Protein Function Prediction using Dependence Maximization
Guoxian Yu, Carlotta Demoniconi, Huzefa Rangwala, and Guoji Zhang
(poster stand #31)

Tue2D: Demo spotlights

Chair: Joaquin Vanschooren and Andreas Hotho
14:15 – 15:55

Image Hub Explorer: Evaluating Representations and Metrics for Content-based Image Retrieval and Object Recognition
Nenad Tomasev and Dunja Mladenic
Ipseity – A Laboratory for Synthesizing and Validating Artificial Cognitive Systems in Multi-Agent Systems
Fabrice Lauri, Nicolas Gaud, Stephane Galland, and Vincent Hilaire
OpenML: A Collaborative Science Platform
Jan Van Rijn, Bernd Bischl, Luis Torgo, Bo Gao, Venkatesh Umaashankar, Simon Fischer, Patrick Winter,Bernd Wiswedel, Michael Berthold, and Joaquin Vanschoren
ViperCharts: Visual Performance Evaluation Platform
Borut Sluban and Nada Lavrac
Targeted Linked Hypernym Discovery: real-time classification of entities in text with Wikipedia
Milan Dojchinovski and Tomas Kliegr
Hermoupolis: A Trajectory Generator for Simulating Generalized Mobility Patterns
Nikos Pelekis, Christos Ntrigkogias, Panagiotis Tampakis, Stylianos Sideridis, and Yannis Theodoridis
AllAboard: a system for exploring urban mobility and optimizing public transport using cellphone data
Michele Berlingerio, Francesco Calabrese, Giusy Di Lorenzo, Rahul Nair, Fabio Pinelli, and Marco Sbodio
ScienScan — an efficient visualization and browsing tool for academic search
Daniil Mirylenka and Andrea Passerini
InVis: A Tool for Interactive Visual Data Analysis
Daniel Paurat and Thomas Gaertner
Kanopy: Analysing the Semantic Network around Document Topics
Ioana Hulpus, Conor Hayes, Marcel Karnstedt, Derek Greene, and Marek Jozwowicz
SCCQL: a Constraint-based Clustering System
Antoine Adam, Hendrik Blockeel, Sander Govers, and Abram Aertsen

Tue3A: Inverse RL & RL Applications

Chair: Kurt Driessens
16:25 – 18:05

A cascaded supervised learning approach to inverse reinforcement learning
Edouard Klein, Bilal Piot, Matthieu Geist, and Olivier Pietquin
(poster stand #32)
Learning from demonstrations: is it worth estimating a reward function?
Bilal Piot, Matthieu Geist, and Olivier Pietquin
(poster stand #33)
Recognition of agents based on observation of their sequential behavior
Qifeng Qiao and Peter Beling
(poster stand #34)
Learning throttle valve control using policy search
Bastian Bischoff, Duy Nguyen-Tuong, Torsten Koller, Heiner Markert, and Alois Knoll
(poster stand #35)
Model-selection for non-parametric function approximation in continuous control systems: A case study in a smart energy system
Daniel Urieli and Peter Stone
(poster stand #36)

Tue3B: Matrix Analysis

Chair: Pauli Miettinen
16:25 – 18:05

Noisy matrix completion using alternating minimization
Suriya Gunasekar, Ayan Acharya, Neeraj Gaur, and Joydeep Ghosh
(poster stand #37)
A nearly unbiased matrix completion approach
Dehua Liu, Tengfei Zhou, Hui Qian, Congfu Xu, and Zhihua Zhang
(poster stand #38)
A counterexample for the validity of using nuclear norm as a convex surrogate of rank
Hongyang Zhang, Zhouchen Lin, and Chao Zhang
(poster stand #39)
Efficient rank-one residue approximation method for graph regularized non-negative matrix factorization
Qing LIAO and Qian Zhang
(poster stand #40)
Maximum entropy models for iteratively identifying subjectively interesting structure in real-valued data
Kleanthis-Nikolaos Kontonasios, Jilles Vreeken,and Tijl De Bie
(poster stand #41)

Tue3C: Applications

Chair: Bernhard Pfahringer
16:25 – 18:05

Incremental Sensor Placement Optimization on Water Network
Xiaomin Xu, Yiqi Lu, Sheng Huang, Yanghua Xiao, and Wei Wang
(poster stand #42)
Detecting Marionette Microblog Users for Improved Information Credibility
Xian Wu, Ziming Feng, Wei Fan, Jing Gao, and Yong Yu
(poster stand #43)
Will my Question be Answered? Predicting “Question Answerability” in Community Question-Answering Sites
Gideon Dror, Yoelle Maarek, and Idan Szpektor
(poster stand #44)
Learning to Detect Patterns of Crime
Tong Wang, Cynthia Rudin, Dan Wagner, and Rich Sevieri
(poster stand #45)
Space Allocation in the Retail Industry: A Decision Support System Integrating Evolutionary Algorithms and Regression Models
Fabio Pinto and Carlos Soares
(poster stand #46)

Tue3D: Semi-supervised Learning

Chair: Thomas Gärtner
16:25 – 18:05

Exploratory Learning
Bhavana Dalvi, William Cohen, and Jamie Callan
(poster stand #47)
Semi-supervised Gaussian Process Ordinal Regression
Srijith P. K., Shirish Shevade, and Sundararajan S.
(poster stand #48) Implementation
Influence of Graph Construction on Semi-supervised Learning
Celso Andre De Sousa, Gustavo Batista, and Solange Rezende
(poster stand #49)
Tractable Semi-Supervised Learning of Complex Structured Prediction Models
Kai-Wei Chang, Sundararajan S., and Sathiya Keerthi
(poster stand #50)
PSSDL: Probabilistic semi-supervised dictionary learning
Behnam Babagholami-Mohamadabadi, Ali Zarghami, Mohammadreza Zolfaghari, and Mahdieh Soleymani Baghshah
(poster stand #51)

Wednesday 25th September

Wed1A: Nectar (1)

Chair: Rosa Meo and Michele Sebag

10:30 – 12:10

Towards Robot Skill Learning: From Simple Skills to Table Tennis
Jan Peters, Katharina Muelling, Jens Kober, Oliver Kroemer, and Gerhard Neumann
Functional MRI Analysis with Sparse Models
Irina Rish

Wed1B: Active Learning and Optimization

Chair: Andrea Passerini

10:30 – 12:10

A Lipschitz Exploration-Exploitation Scheme for Bayesian Optimization
Ali Jalali, Javad Azimi, Xiaoli Fern, and Ruofei Zhang
(poster stand #1)
Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration
Emile Contal, David Buffoni, Alexandre Robicquet, and Nicolas Vayatis
(poster stand #2) Implementation
Regret bounds for reinforcement learning with policy advice
Mohammad Azar, Alessandro Lazaric, and Emma Brunskill
(poster stand #3)
A time and space efficient algorithm for contextual linear bandits
Jose Bento, Stratis Ioannidis, S Muthukrishnan, and Jinyun Yan
(poster stand #4)
Knowledge transfer for multi-labeler active learning
Meng Fang, Jie Yin, and Xingquan Zhu
(poster stand #5)

Wed1C: Networks (2)

Chair: Jan Ramon
10:30 – 11:55

ABACUS: Frequent Pattern Mining Based Community Discovery in Multidimensional Networks*
Michele Berlingerio, Fabio Pinelli, and Francesco Calabrese
(poster stand #6)
Discovering Nested Communities
Nikolaj Tatti and Aristides Gionis
(poster stand #7)
CSI: Community-level Social Influence analysis
Yasir Mehmood, Nicola Barbieri, Francesco Bonchi, and Antti Ukkonen
(poster stand #8)
Community Distribution Outlier Detection in Heterogeneous Information Networks
Manish Gupta, Jing Gao, and Jiawei Han
(poster stand #9) Implementation

Wed1D: Structured Output, Multi-task

Chair: Manfred Jaeger
10:30 – 12:10

Taxonomic prediction with tree-structured covariances
Matthew Blaschko, Wojciech Zaremba, and Arthur Gretton
(poster stand #10) Implementation
Position preserving multi-output prediction
Zubin Abraham and Pang-Ning Tan
(poster stand #11)
Structured output learning with candidate labels for local parts
Chengtao Li, Jianwen Zhang, and Zheng Chen
(poster stand #12)
Shared structure learning for multiple tasks with multiple views
Xin Jin, Fuzhen Zhuang, Shuhui Wang, Qing He, and Zhongzhi Shi
(poster stand #13) Implementation
Using both latent and supervised shared topics for multi-task learning
Ayan Acharya, Aditya Rawal, Eduardo Hruschka, and Raymond Mooney
(poster stand #14)

Wed2A: Nectar (2)

Chair: Rosa Meo and Michele Sebag

14:00 – 15:40

A theoretical framework for exploratory data mining: recent insights and challenges ahead
Tijl De Bie and Eirini Spyropoulou
Tensor Factorization for Multi-Relational Learning
Maximilian Nickel and Volker Tresp
MONIC – Modeling and Monitoring Cluster Transitions
Myra Spiliopoulou, Eirini Ntoutsi, Yannis Theodoridis, and Rene Schult

Wed2B: Models for Sequential Data

Chair: Eyke Hüllermeier
14:00 – 15:40

Spectral learning of sequence taggers over continuous sequences
Ariadna Quattoni and Adria Recasens
(poster stand #15)
Fast variational bayesian linear state-space model
Jaakko Luttinen
(poster stand #16) Implementation
Inhomogeneous parsimonious Markov models
Ralf Eggeling, Andre Gohr, Pierre-Yves Bourguignon, Edgar Wingender, and Ivo Grosse
(poster stand #17)
Future locations prediction with uncertain data
Disheng Qiu, Paolo Papotti, and Blanco Lorenzo
(poster stand #18)
Modeling short-term energy load with continuous conditional random fields
Hongyu Guo
(poster stand #19)

Wed2C: Graph Mining

Chair: Toon Calders
14:00 – 15:25

Activity Preserving Graph Simplification*
Francesco Bonchi, Gianmarco De Francisci Morales, Aristides Gionis, and Antti Ukkonen
(poster stand #20)
A Fast Approximation of the Weisfeiler-Lehman Graph Kernel for RDF Data
Gerben De Vries
(poster stand #21) Implementation
Improving relational classification using link prediction techniques
Cristina Perez-Sola and Jordi Herrera-Joancomarti
(poster stand #22)
Efficient Frequent Connected Induced Subgraph Mining in Graphs of Bounded Treewidth
Tamas Horvath, Keisuke Otaki, and Jan Ramon
(poster stand #23)

Wed2D: Natural Language Processing & Probabilistic Models

14:00 – 15:40

Supervised Learning of Syntactic Contexts for Uncovering Definitions and Extracting Hypernym Relations in Text Databases
Guido Boella and Luigi Di Caro
(poster stand #24)
Error Prediction With Partial Feedback
William Darling, Guillaume Bouchard, Shachar Mirkin, and Cedric Archambeau
(poster stand #25)
Boot-Strapping Language Identifiers for Short Colloquial Postings
Moises Goldszmidt, Marc Najork, and Stelios Paparizos
(poster stand #26) Implementation
A bayesian classifier for learning from tensorial data
Wei Liu, Jeffrey Chan, James Bailey, Christopher Leckie, Fang Chen, and Rao Kotagiri
(poster stand #27)
Prediction with model based neutrality
Kazuto Fukuchi, Jun Sakuma, and Toshihiro Kamishima
(poster stand #28)

Wed3A: Subgroup Discovery & Streams

Chair: Nada Lavrac
16:10 – 17:50

Discovering skylines of subgroup sets
Matthijs van Leeuwen and Antti Ukkonen
(poster stand #29)
Difference-based estimates for generalization-aware subgroup discovery
Florian Lemmerich, Martin Becker, and Frank Puppe
(poster stand #30)
Fast and exact mining of probabilistic data streams
Reza Akbarinia and Florent Masseglia
(poster stand #31)
Pitfalls in benchmarking data stream classification and how to avoid them
Albert Bifet, Jesse Read, Indre Zliobaite, Bernhard Pfahringer, and Geoff Holmes
(poster stand #32)
Adaptive model rules from high-speed data streams
Ezilda Almeida, Carlos Ferreira, and Joao Gama
(poster stand #33)

Wed3B: Multi-label Classification & Outlier Detection

Chair: Luis Torgo
16:10 – 17:50

Multi-label classification with output kernels
Yuhong Guo and Dale Schuurmans
(poster stand #34)
Probabilistic clustering for hierarchical multi-label classification of protein functions
Rodrigo Barros, Ricardo Cerri, Alex Freitas, and Andre Carvalho
(poster stand #35)
Mining outlier participants: insights using directional distributions in latent models
Didi Surian and Sanjay Chawla
(poster stand #36)
Anomaly detection in vertically partitioned data by distributed core vector machines
Marco Stolpe, Kanishka Bhaduri, Kamalika Das, and Katharina Morik
(poster stand #37)
Local outlier detection with interpretation
Xuan-Hong Dang, Barbora Micenkova, Ira Assent, and Raymond T. Ng
(poster stand #38)

Wed3C: Ensembles

Chair: Geoff Holmes
16:10 – 17:50

Boosting for unsupervised domain adaptation
Amaury Habrard, Jean-Philippe Peyrache, and Marc Sebban
(poster stand #39)
AR-Boost: Reducing Overfitting by a Robust Data-Driven Regularization Strategy
Baidya Nath Saha, Gautam Kunapuli, Nilanjan Ray, Joseph Maldjian, and Sriraam Natarajan
(poster stand #40)
Parallel Boosting with Momentum
Indraneel Mukherjee, Yoram Singer, Rafael Frongillo, and Kevin Canini
(poster stand #41)
Inner Ensembles: Using Ensemble Methods in the Learning Phase
Houman Abbasian, Chris Drummond, Nathalie Japkowicz, and Stan Matwin
(poster stand #42)
Mixtures of Large Margin Nearest Neighbor Classifiers
Murat Semerci, and Ethem Alpaydin
(poster stand #43)

Wed3D: Bayesian Learning

Chair: Roni Khardon
16:10 – 17:35

A Comparative Evaluation of Stochastic-based Inference Methods for Gaussian Process Models*
Maurizio Filippone, Mingjun Zhong, and Mark Girolami
(poster stand #44)
Decision-theoretic Sparsification for Gaussian Process Preference Learning
Ehsan Abbasnejad, Edwin Bonilla, and Scott Sanner
(poster stand #45)
Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures
Konstantinos Bousmalis, Stefanos Zafeiriou, Louis-Philippe Morency, Maja Pantic, and Zoubin Ghahramani
(poster stand #46)
Sparsity in Bayesian Blind Source Separation and Deconvolution
Vaclav Smidl and Ondrej Tichy
(poster stand #47)

Thursday 26th September

Thu1A: Industrial track (1)

Chair: Bernhard Pfahringe

11:00 – 12:25

Some of the Problems and Applications of Opinion Analysis
Hugo Zaragoza
Machine Learning in a large diversified Internet Group
Jean-Paul Schmetz

Thu1B: Sequential Pattern Mining

Chair: Donata Malerba
11:00 – 12:20

Itemset Based Sequence Classification
Cheng Zhou, Boris Cule, and Bart Goethals
(poster stand #48) Implementation
A relevance criterion for sequential patterns
Henrik Grosskreutz, Bastian Lang, and Daniel Trabold
(poster stand #49)
A fast and simple method for mining subsequences with surprising event counts
Jefrey Lijffijt
(poster stand #50)
Relevant subsequence detection with sparse dictionary learning
Sam Blasiak, Huzefa Rangwala,and Kathryn Laskey
(poster stand #51)

Thu1C: Graphical Models

Chair: Sangkyun Lee
11:00 – 12:25

Spatio-Temporal Random Fields: Compressible Representation and Distributed Estimation*
Nico Piatkowski, Sangkyun Lee, and Katharina Morik
(poster stand #52) Implementation
Knowledge intensive learning: combining qualitative constraints with causal independence for parameter learning in probabilistic models
Shuo Yang and Sriraam Natarajan
(poster stand #53)
Direct learning of sparse changes in Markov networks by density ratio ratio estimation
Song Liu, John Quinn, Michael Gutmann, and Masashi Sugiyama
(poster stand #54) Implementation
Greedy part-wise learning of sum-product networks
Robert Peharz, Bernhard Geiger, and Franz Pernkopf
(poster stand #55)

Thu1D: Unsupervised Learning

Chair: Volker Tresp
11:00 – 12:25

A Framework for Semi-Supervised and Unsupervised Optimal Extraction of Clusters from Hierarchies*
Ricardo J.G.B. Campello, Davoud Moulavi, Arthur Zimek, and Jorg Sander
(poster stand #56)
Minimal Shrinkage for Noisy Data Recovery
Deguang Kong and Chris Ding
(poster stand #57)
Reduced-Rank Local Distance Metric Learning
Yinjie Huang, Cong Li, Michael Georgiopoulos, and Georgios Anagnostopoulos
(poster stand #58)
Cross-Domain Recommendation via Cluster-Level Latent Factor Model
Sheng Gao, Hao Luo, Da Chen, Shantao Li, Patrick Gallinar, and Jun Guo
(poster stand #59)

Thu2A: Industrial track (2)

Chair: Thomas Gärtner

14:15 – 15:40

Bayesian Learning in Online Service: Statistics Meets Systems
Ralf Herbrich
ML and Business: A Love-Hate Relationship
Andreas Antrup

Thu2B: Dynamic Graphs

Chair: Myra Spiliopoulou
14:15 – 15:35

Incremental Local Evolutionary Outlier Detection for Dynamic Social Networks
Tengfei Ji, Jun Gao, and Dongqing Yang
(poster stand #60)
Continuous Similarity Computation over Streaming Graphs
Elena Valari and Apostolos Papadopoulos
(poster stand #61)
Trend Mining in Dynamic Attributed Graphs
Elise Desmier, Marc Plantevit, Celine Robardet, and Jean-Francois Boulicaut
(poster stand #62)
How long will she call me? Distribution, Social Theory and Duration Prediction
Yuxiao Dong, Jie Tang, Tiancheng Lou, Bin Wu, and Nitesh Chawla
(poster stand #63) Implementation

Thu2C: Statistical Learning (1)

Chair: Paolo Frasconi
14:15 – 15:40

Block coordinate descent algorithms for large-scale sparse multiclass classification*
Mathieu Blondel, Kazuhiro Seki, and Kuniaki Uehara
(poster stand #64) Implementation
MORD: Multi-class classifier for Ordinal Regression
Konstiantyn Antoniuk, Vojtech Franc, and Vaclav Hlavac
(poster stand #65)
Identifiability of Model Properties in Over-Parameterized Model Classes
Manfred Jaeger
(poster stand #66)
Multi-core structural SVM training
Kai-Wei Chang, Vivek srikumar, and Dan Roth
(poster stand #67)

Thu2D: Evaluation & kNN

Chair: Johannes Furnkranz
14:15 – 15:40

ROC Curves in Cost Space*
Cesar Ferri, Jose Hernandez-Orallo, and Peter Flach
(poster stand #68)
Area Under the Precision-Recall Curve: Point Estimates and Confidence Intervals
(A typo appearing in the published paper is corrected in the linked pdf)
Kendrick Boyd, Kevin Eng, and David Page
(poster stand #69)
Hub Co-occurrence Modeling for Robust High-dimensional kNN Classification
Nenad Tomasev and Dunja Mladenic
(poster stand #70)
Fast kNN Graph Construction with Locality Sensitive Hashing
Yan-Ming Zhang, Kaizhu Huang, Guanggang Geng, and Cheng-Lin Liu
(poster stand #71)

Thu3A: Sequence & Time Series Analysis

Chair: Mark Last
16:10 – 17:35

Fast Sequence Segmentation using Log-Linear Models*
Nikolaj Tatti
(poster stand #72)
Explaining interval sequences by randomization
Andreas Henelius, Jussi Korpela, and Kai Puolamaki
(poster stand #73)
A layered Dirichlet process for hierarchical segmentation of sequential grouped data
Adway Mitra, Ranganath B.N., and Indrajit Bhattacharya
(poster stand #74)
Fault tolerant regression for sensor data
Indre Zliobaite and Jaakko Hollmen
(poster stand #75)

Thu3B: Declarative Data Mining & Meta Learning

Chair: Luc De Raedt
16:10 – 17:35

Pairwise Meta-Rules for Better Meta-Learning-Based Algorithm Ranking*
Quan Sun and Bernhard Pfahringer
(poster stand #76)
SNNAP: Solver-based nearest neighbor for algorithm portfolios
Marco Collautti, Yuri Malitsky, and Barry O’Sullivan
(poster stand #77) Implementation
Top-k frequent closed item set mining using top-k-SAT problem
Said Jabbour, Lakhdar Sais, and Yakoub Salhi
(poster stand #78)
A declarative framework for constrained clustering
Thi-Bich-Hanh Dao, Khanh-Chuong Duong, and Christel Vrain
(poster stand #79)

Thu3C: Topic Models

Chair: Edwin Bonilla
16:10 – 17:35

Probabilistic Topic Models for Sequence Data*
Nicola Barbieri, Antonio Bevacqua, Marco Carnuccio, Giuseppe Manco, and Ettore Ritacco
(poster stand #80)
Nested hierarchical Dirichlet processes for nonparametric entity-topic analysis
Priyanka Agrawal, Lavanya Tekumalla, and Indrajit Bhattacharya
(poster stand #81)
From topic models to semi-supervised learning: biased mixed-membership models to exploit topic-indicative features in entity clustering
Ramnath Balasubramanyan, William Cohen, and Bhavana Dalvi
(poster stand #82)
Sparse relational topic models for document networks
Aonan Zhang, Jun Zhu, and Bo Zhang
(poster stand #83)

Thu3D: Statistical Learning (2)

Chair: Dale Schuurmans
16:10 – 17:35

The flip-the-state transition operator for restricted Boltzmann machines*
Kai Brugge, Asja Fischer, and Christian Igel
(poster stand #84)
Learning Discriminative Sufficient Statistics Score Space
Xiong Li, Bin Wang, Yuncai Liu, and Tai Sing Lee
(poster stand #85)
The stochastic gradient descent for the primal L1-SVM optimization revisited
Constantinos Panagiotakopoulos and Petroula Tsampouka
(poster stand #86) Implementation
Bundle CDN: A Highly Parallelized Approach for Large-scale L1-regularized Logistic Regression
Yatao Bian, Xiong Li, mingqi Cao, and Yuncai Liu
(poster stand #87)

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