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A First Course in Electrical and Computer Engineering
Published 2009Access online version
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Computer Aided Verification 33rd International Conference, CAV 2021, Virtual Event, July 20-23, 2021, Proceedings, Part II /
Published 2021Table of Contents: “…Complexity and Termination -- Learning Probabilistic Termination Proofs -- Ghost Signals: Verifying Termination of Busy Waiting -- Reflections on Termination of Linear Loops -- Decision Tree Learning in CEGIS-Based Termination Analysis -- ATLAS: Automated Amortised Complexity Analysis of Self-Adjusting Data Structures -- Decision Procedures and Solvers -- Theory Exploration Powered by Deductive Synthesis -- CoqQFBV: A Scalable Certified SMT Quantifier-Free Bit-Vector Solver -- Porous Invariants -- JavaSMT 3: Interacting with SMT Solvers in Java -- Efficient SMT-based Analysis of Failure Propagation -- ToolX : Better Delta Debugging for the SMT-LIBv2 Language and Friends -- Learning Union of Integer Hypercubes with Queries (with applications to monadic decomposition) -- Interpolation and Model Checking for Nonlinear Arithmetic -- An SMT Solver for Regular Expressions and Linear Arithmetic over String Length -- Counting Minimal Unsatisfiable Subsets -- Sound Verification Procedures for Temporal Properties of Infinite-State Systems -- Hardware and Model Checking -- Progress in Certifying Hardware Model Checking Results -- Model-Checking Structured Context-Free Languages -- Model Checking ! …”
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Advances in Intelligent Data Analysis XVIII 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27-29, 2020, Proceedings /
Published 2020Table of Contents: “…Multivariate Time Series as Images: Imputation Using Convolutional Denoising Autoencoder -- Dual Sequential Variational Autoencoders for Fraud Detection -- A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks -- Efficient Batch-Incremental Classification Using UMAP for Evolving Data Streams -- GraphMDL: Graph Pattern Selection Based on Minimum Description Length -- Towards Content Sensitivity Analysis -- Gibbs Sampling Subjectively Interesting Tiles -- Even Faster Exact k-Means Clustering -- Ising-Based Consensus Clustering on Special Purpose Hardware -- Transfer Learning by Learning Projections from Target to Source -- Computing Vertex-Vertex Dissimilarities Using Random Trees: Application to Clustering in Graphs -- Towards Evaluation of CNN Performance in Semantically Meaningful Latent Spaces -- Vouw: Geometric Pattern Mining Using the MDL Principle -- A Consensus Approach to Improve NMF Document Clustering -- Discriminative Bias for Learning Probabilistic Sentential Decision Diagrams -- Widening for MDL-Based Retail Signature Discovery -- Addressing the Resolution Limit and the Field of View Limit in Community Mining -- Estimating Uncertainty in Deep Learning for Reporting Confidence: An Application on Cell Type Prediction in Testes Based on Proteomics -- Adversarial Attacks Hidden in Plain Sight -- Enriched Weisfeiler-Lehman Kernel for Improved Graph Clustering of Source Code -- Overlapping Hierarchical Clustering (OHC) -- Digital Footprints of International Migration on Twitter -- Percolation-Based Detection of Anomalous Subgraphs in Complex Networks -- A Late-Fusion Approach to Community Detection in Attributed Networks -- Reconciling Predictions in the Regression Setting: an Application to Bus Travel Time Prediction -- A Distribution Dependent and Independent Complexity Analysis of Manifold Regularization -- Actionable Subgroup Discovery and Urban Farm Optimization -- AVATAR - Machine Learning Pipeline Evaluation Using Surrogate Model -- Detection ofDerivative Discontinuities in Observational Data -- Improving Prediction with Causal Probabilistic Variables -- DO-U-Net for Segmentation and Counting -- Enhanced Word Embeddings for Anorexia Nervosa Detection on Social Media -- Event Recognition Based on Classification of Generated Image Captions -- Human-to-AI Coach: Improving Human Inputs to AI Systems -- Aleatoric and Epistemic Uncertainty with Random Forests -- Master your Metrics with Calibration -- Supervised Phrase-Boundary Embeddings -- Predicting Remaining Useful Life with Similarity-Based Priors -- Orometric Methods in Bounded Metric Data -- Interpretable Neuron Structuring with Graph Spectral Regularization -- Comparing the Preservation of Network Properties by Graph Embeddings -- Making Learners (More) Monotone -- Combining Machine Learning and Simulation to a Hybrid Modelling Approach -- LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification -- Angle-Based Crowding Degree Estimation for Many-Objective Optimization.…”
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