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1
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A Cascaded Supervised Learning Approach to Inverse Reinforcement Learning
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1
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AR-Boost: Reducing Overfitting by a Robust Data-Driven Regularization Strategy
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1
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Incremental Local Evolutionary Outlier Detection for Dynamic Social Networks
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16
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How Long Will She Call Me? Distribution, Social Theory and Duration Prediction
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17
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Learning from Demonstrations: Is It Worth Estimating a Reward Function?
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17
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Parallel Boosting with Momentum
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32
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Discovering Nested Communities
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33
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Inner Ensembles: Using Ensemble Methods Inside the Learning Algorithm
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33
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Recognition of Agents Based on Observation of Their Sequential Behavior
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48
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CSI: Community-Level Social Influence Analysis
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49
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Learning Discriminative Sufficient Statistics Score Space for Classification
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49
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Learning Throttle Valve Control Using Policy Search
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64
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Supervised Learning of Syntactic Contexts for Uncovering Definitions and Extracting Hypernym Relations in Text Databases
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65
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Model-Selection for Non-parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System
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65
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The Stochastic Gradient Descent for the Primal L1-SVM Optimization Revisited
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80
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Error Prediction with Partial Feedback
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81
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Bundle CDN: A Highly Parallelized Approach for Large-Scale ℓ<Subscript>1</Subscript>-Regularized Logistic Regression
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81
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Learning Graph-Based Representations for Continuous Reinforcement Learning Domains
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95
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Boot-Strapping Language Identifiers for Short Colloquial Postings
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96
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MORD: Multi-class Classifier for Ordinal Regression
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97
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Regret Bounds for Reinforcement Learning with Policy Advice
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112
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A Pairwise Label Ranking Method with Imprecise Scores and Partial Predictions
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112
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Identifiability of Model Properties in Over-Parameterized Model Classes
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113
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Exploiting Multi-step Sample Trajectories for Approximate Value Iteration
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128
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Exploratory Learning
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128
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Learning Socially Optimal Information Systems from Egoistic Users
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129
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Expectation Maximization for Average Reward Decentralized POMDPs
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144
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Semi-supervised Gaussian Process Ordinal Regression
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145
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Properly Acting under Partial Observability with Action Feasibility Constraints
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145
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Socially Enabled Preference Learning from Implicit Feedback Data
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160
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Influence of Graph Construction on Semi-supervised Learning
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161
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Cross-Domain Recommendation via Cluster-Level Latent Factor Model
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162
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Iterative Model Refinement of Recommender MDPs Based on Expert Feedback
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176
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Tractable Semi-supervised Learning of Complex Structured Prediction Models
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177
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Minimal Shrinkage for Noisy Data Recovery Using Schatten-<Emphasis Type="Italic">p</Emphasis> Norm Objective
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178
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Solving Relational MDPs with Exogenous Events and Additive Rewards
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192
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PSSDL: Probabilistic Semi-supervised Dictionary Learning
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194
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Continuous Upper Confidence Trees with Polynomial Exploration – Consistency
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194
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Noisy Matrix Completion Using Alternating Minimization
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208
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Embedding with Autoencoder Regularization
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210
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A Lipschitz Exploration-Exploitation Scheme for Bayesian Optimization
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210
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A Nearly Unbiased Matrix Completion Approach
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224
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Reduced-Rank Local Distance Metric Learning
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225
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Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration
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226
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A Counterexample for the Validity of Using Nuclear Norm as a Convex Surrogate of Rank
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240
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Learning Exemplar-Represented Manifolds in Latent Space for Classification
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241
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Greedy Confidence Pursuit: A Pragmatic Approach to Multi-bandit Optimization
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242
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Efficient Rank-one Residue Approximation Method for Graph Regularized Non-negative Matrix Factorization
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256
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Locally Linear Landmarks for Large-Scale Manifold Learning
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256
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Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued Data
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257
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A Time and Space Efficient Algorithm for Contextual Linear Bandits
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272
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An Analysis of Tensor Models for Learning on Structured Data
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272
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Discovering Skylines of Subgroup Sets
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273
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Knowledge Transfer for Multi-labeler Active Learning
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288
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Difference-Based Estimates for Generalization-Aware Subgroup Discovery
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288
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Learning Modewise Independent Components from Tensor Data Using Multilinear Mixing Model
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289
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Spectral Learning of Sequence Taggers over Continuous Sequences
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304
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Local Outlier Detection with Interpretation
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304
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Taxonomic Prediction with Tree-Structured Covariances
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305
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Fast Variational Bayesian Linear State-Space Model
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320
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Position Preserving Multi-Output Prediction
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321
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Anomaly Detection in Vertically Partitioned Data by Distributed Core Vector Machines
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321
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Inhomogeneous Parsimonious Markov Models
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336
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Structured Output Learning with Candidate Labels for Local Parts
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337
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Explaining Interval Sequences by Randomization
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337
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Mining Outlier Participants: Insights Using Directional Distributions in Latent Models
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353
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Anonymizing Data with Relational and Transaction Attributes
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353
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Itemset Based Sequence Classification
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353
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Shared Structure Learning for Multiple Tasks with Multiple Views
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369
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A Relevance Criterion for Sequential Patterns
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369
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Using Both Latent and Supervised Shared Topics for Multitask Learning
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370
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Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings
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385
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A Fast and Simple Method for Mining Subsequences with Surprising Event Counts
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385
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Probabilistic Clustering for Hierarchical Multi-Label Classification of Protein Functions
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387
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Evasion Attacks against Machine Learning at Test Time
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401
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Multi-core Structural SVM Training
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401
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Relevant Subsequence Detection with Sparse Dictionary Learning
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403
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The Top-<Emphasis Type="Italic">k</Emphasis> Frequent Closed Itemset Mining Using Top-<Emphasis Type="Italic">k</Emphasis> SAT Problem
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417
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Future Locations Prediction with Uncertain Data
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417
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Multi-label Classification with Output Kernels
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419
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A Declarative Framework for Constrained Clustering
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433
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Boosting for Unsupervised Domain Adaptation
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433
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Modeling Short-Term Energy Load with Continuous Conditional Random Fields
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435
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SNNAP: Solver-Based Nearest Neighbor for Algorithm Portfolios
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449
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Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines
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449
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Fault Tolerant Regression for Sensor Data
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451
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Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals
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465
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A Layered Dirichlet Process for Hierarchical Segmentation of Sequential Grouped Data
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465
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Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them
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467
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Incremental Sensor Placement Optimization on Water Network
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480
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Adaptive Model Rules from Data Streams
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483
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A Bayesian Classifier for Learning from Tensorial Data
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483
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Detecting Marionette Microblog Users for Improved Information Credibility
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493
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Fast and Exact Mining of Probabilistic Data Streams
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499
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Prediction with Model-Based Neutrality
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499
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Will My Question Be Answered? Predicting “Question Answerability” in Community Question-Answering Sites
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509
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Detecting Bicliques in GF[q]
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515
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Decision-Theoretic Sparsification for Gaussian Process Preference Learning
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515
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Learning to Detect Patterns of Crime
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525
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As Strong as the Weakest Link:Mining Diverse Cliques in Weighted Graphs