Search Results - empirical algorithmics

Computational phraseology

Table of Contents: “…Monocollocable words : a type of language combinatory periphery / František Čermák -- Translation asymmetries of multiword expressions in machine translation : an analysis of the TED-MWE corpus / Johanna Monti, Mihael Arcan and Federico Sangati -- German constructional phrasemes and their Russian counterparts : a corpus-based study / Dmitrij Dobrovol'skij -- Computational phraseology and translation studies : from theoretical hypotheses to practical tools / Jean-Pierre Colson -- Computational extraction of formulaic sequences from corpora : two case studies of a new extraction algorithm / Alexander Wahl and Stefan Th. Gries -- Computational phraseology discovery in corpora with the MWETOOLKIT / Carlos Ramisch -- Multiword expressions in comparable corpora / Peter Ďurčo -- Collecting collocations from general and specialised corpora : a comparative analysis / Marie-Claude L'Homme and Daphnée Azoulay -- What matters more : the size of the corpora or their quality? …”
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Applications of GRA and grey prediction models

Table of Contents: “…Cover; Editorial advisory board; Guest editorial; Property of derived grey verhulst model with multiple transformation; Multi-phase information aggregation and dynamic synthetic evaluation based on grey inspiriting control lines; Multi-terms MADM procedures with GRA and TOPSIS based on IFS and IVIFS; Development prediction of logistics industry in Henan province and its dynamic analysis; A grey STA-GERT quality evaluation model for complex products based on manufacture-service dual-network; Theoretical and empirical analysis of the supplier induced demand in health care marketin China.…”
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The handbook of news analytics in finance

Table of Contents: “…Kalev and Huu Nhan Duong -- Equity portfolio risk estimation using market information and sentiment / Leela Mitra, Gautam Mitra and Dan diBartolomeo -- Incorporating news into algorithmic trading strategies : increasing the signal-to-noise ratio / Richard Brown -- Are you still trading without news? …”
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Neural networks in chemical reaction dynamics

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A practitioner's guide to asset allocation by Kinlaw, William, Kinlaw, William, Kritzman, Mark P., Turkington, David, 1983-

Table of Contents: “…-- Linear Hedging Strategies -- Nonlinear Hedging Strategies -- Economic Intuition -- References -- Notes -- Chapter 11: Illiquidity -- The Challenge -- Shadow Assets and Liabilities -- Expected Return and Risk of Shadow Allocations -- Other Considerations -- Case Study -- The Bottom Line -- Appendix -- References -- Notes -- Chapter 12: Risk in the Real World -- The Challenge -- End-of-Horizon Exposure to Loss -- Within-Horizon Exposure to Loss -- Regimes -- The Bottom Line -- References -- Notes -- Chapter 13: Estimation Error -- The Challenge -- Traditional Approaches to Estimation Error -- Stability-Adjusted Optimization -- Building a Stability-Adjusted Return Distribution -- Determining the Optimal Allocation -- Empirical Analysis -- The Bottom Line -- References -- Notes -- Chapter 14: Leverage versus Concentration -- The Challenge -- Leverage in Theory -- Leverage in Practice -- The Bottom Line -- References -- Notes -- Chapter 15: Rebalancing -- The Challenge -- The Dynamic Programming Solution -- The Markowitz-van Dijk Heuristic -- The Bottom Line -- References -- Notes -- Chapter 16: Regime Shifts -- The Challenge -- Predictability of Return and Risk -- Regime-Sensitive Allocation -- Tactical Asset Allocation -- The Bottom Line -- Appendix: Baum-Welch Algorithm -- References -- Notes -- Section Four: Addendum -- Chapter 17: Key Takeaways.…”
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The silicon jungle : a novel of deception, power, and Internet intrigue by Baluja, Shumeet, 1971-

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Genomic Signal Processing. by Shmulevich, Ilya

Table of Contents: “…5.2 Complexity Regularization5.2.1 Regularization of the Error; 5.2.2 Structural Risk Minimization; 5.2.3 Empirical Complexity ; 5.3 Feature Selection; 5.3.1 Peaking Phenomenon; 5.3.2 Feature Selection Algorithms; 5.3.3 Impact of Error Estimation on Feature Selection; 5.3.4 Redundancy; 5.3.5 Parallel Incremental Feature Selection; 5.3.6 Bayesian Variable Selection; 5.4 Feature Extraction; Bibliography; 6 Clustering; 6.1 Examples of Clustering Algorithms; 6.1.1 Euclidean Distance Clustering; 6.1.2 Self-Organizing Maps; 6.1.3 Hierarchical Clustering; 6.1.4 Model-Based Cluster Operators.…”
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Mechanisms and games for dynamic spectrum allocation

Table of Contents: “…7.3.10 Other equilibrium concepts -- 7.4 Learning equilibria -- 7.4.1 Learning Nash equilibria -- 7.4.2 Learning epsilon-equilibrium -- 7.4.3 Learning coarse correlated equilibrium -- 7.4.4 Learning satisfaction equilibrium -- 7.4.5 Discussion -- 7.5 Conclusion -- References -- II Cognitive radio and sharing of unlicensed spectrum -- 8 Cooperation in cognitiveradio networks: from accessto monitoring -- 8.1 Introduction -- 8.1.1 Cooperation in cognitive radio: mutual benefits and costs -- 8.2 An overview of coalitional game theory -- 8.3 Cooperative spectrum exploration and exploitation -- 8.3.1 Motivation -- 8.3.2 Basic problem -- 8.3.3 Joint sensing and access as a cooperative game -- 8.3.4 Coalition formation algorithm for joint sensing and access -- 8.3.5 Numerical results -- 8.4 Cooperative primary user activity monitoring -- 8.4.1 Motivation -- 8.4.2 Primary user activity monitoring: basic model -- 8.4.3 Cooperative primary user monitoring -- 8.4.4 Numerical results -- 8.5 Summary -- Acknowledgements -- Copyright notice -- References -- 9 Cooperative cognitive radios with diffusion networks -- 9.1 Introduction -- 9.2 Preliminaries -- 9.2.1 Basic tools in convex and matrix analysis -- 9.2.2 Graphs -- 9.3 Distributed spectrum sensing -- 9.4 Iterative consensus-based approaches -- 9.4.1 Average consensus algorithms -- 9.4.2 Acceleration techniques for iterative consensus algorithms -- 9.4.3 Empirical evaluation -- 9.5 Consensus techniques based on CoMAC -- 9.6 Adaptive distributed spectrum sensing based on adaptive subgradient techniques -- 9.6.1 Distributed detection with adaptive filters -- 9.6.2 Set-theoretic adaptive filters for distributed detection -- 9.6.3 Empirical evaluation -- 9.7 Channel probing -- 9.7.1 Introduction -- 9.7.2 Admissibility problem -- 9.7.3 Power and admission control algorithms.…”
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Empathic space : the computation of human-centric architecture

Table of Contents: “…Cover; Title Page; Copyright Page; Contents; EDITORIAL; ABOUT THE GUEST-EDITORS; SPOTLIGHT: Visual highlights of the issue; INTRODUCTION: The Space of People in Computation; Theories of Designing Human-Centric Spaces; Developing the Code of Empirical Space; Space as Heuristic Generation; Interactions in the Field; Cognitive Conditions; The New Organic: Anthro-Spatial Planning Systems; Experiential Typologies of Spatial Archetypes; HEURISTIC GENERATION; Generative Design Methods and the Exploration of Worlds of Formal Possibility; Generative Systems for Automated Plan Layout.…”
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Reviews in computational chemistry.

Table of Contents: “…Small Molecule Docking and Scoring; Introduction; Algorithms for Molecular Docking; The Docking Problem; Placing Fragments and Rigid Molecules; Flexible Ligand Docking; Handling Protein Flexibility; Docking of Combinatorial Libraries; Scoring; Shape and Chemical Complementary Scores; Force Field Scoring; Empirical Scoring Functions; Knowledge-Based Scoring Functions; Comparing Scoring Functions in Docking Experiments: Consensus Scoring.…”
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Harry Markowitz : selected works by Markowitz, Harry M., 1927-2023

Table of Contents: “…Computation of mean-semivariance efficient sets by the critical line algorithm. Data mining corrections -- ch. 7. Harry Markowitz Company. …”
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Data Protection and Privacy : the Internet of Bodies. by Leenes, Ronald

Table of Contents: “…Grinding Privacy in the Internet of Bodies: An Empirical Qualitative Research on Dating Mobile Applications for Men Who Have Sex with Men; 1. …”
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Applied Artificial Intelligence : Proceedings of the 7th International FLINS Conference. by Arena, Paolo, Fortuna, Luigi

Table of Contents: “…An extended branch-and-bound algorithm for fuzzy linear bilevel programming / G. …”
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EEG Signal Processing and Machine Learning. by Sanei, Saeid

Table of Contents: “…3.6 Dynamic Modelling of Neuron Action Potential Threshold -- 3.7 Summary -- References -- Chapter 4 Fundamentals of EEG Signal Processing -- 4.1 Introduction -- 4.2 Nonlinearity of the Medium -- 4.3 Nonstationarity -- 4.4 Signal Segmentation -- 4.5 Signal Transforms and Joint Time-Frequency Analysis -- 4.5.1 Wavelet Transform -- 4.5.1.1 Continuous Wavelet Transform -- 4.5.1.2 Examples of Continuous Wavelets -- 4.5.1.3 Discrete-Time Wavelet Transform -- 4.5.1.4 Multiresolution Analysis -- 4.5.1.5 Wavelet Transform Using Fourier Transform -- 4.5.1.6 Reconstruction -- 4.5.2 Synchro-Squeezed Wavelet Transform -- 4.5.3 Ambiguity Function and the Wigner-Ville Distribution -- 4.6 Empirical Mode Decomposition -- 4.7 Coherency, Multivariate Autoregressive Modelling, and Directed Transfer Function -- 4.8 Filtering and Denoising -- 4.9 Principal Component Analysis -- 4.9.1 Singular Value Decomposition -- 4.10 Summary -- References -- Chapter 5 EEG Signal Decomposition -- 5.1 Introduction -- 5.2 Singular Spectrum Analysis -- 5.2.1 Decomposition -- 5.2.2 Reconstruction -- 5.3 Multichannel EEG Decomposition -- 5.3.1 Independent Component Analysis -- 5.3.2 Instantaneous BSS -- 5.3.3 Convolutive BSS -- 5.3.3.1 General Applications -- 5.3.3.2 Application of Convolutive BSS to EEG -- 5.4 Sparse Component Analysis -- 5.4.1 Standard Algorithms for Sparse Source Recovery -- 5.4.1.1 Greedy-Based Solution -- 5.4.1.2 Relaxation-Based Solution -- 5.4.2 k-Sparse Mixtures -- 5.5 Nonlinear BSS -- 5.6 Constrained BSS -- 5.7 Application of Constrained BSS -- Example -- 5.8 Multiway EEG Decompositions -- 5.8.1 Tensor Factorization for BSS -- 5.8.2 Solving BSS of Nonstationary Sources Using Tensor Factorization -- 5.9 Tensor Factorization for Underdetermined Source Separation -- 5.10 Tensor Factorization for Separation of Convolutive Mixtures in the Time Domain.…”
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Current development of mechanical engineering and energy : selected, peer reviewed papers from the 2013 International Symposium on Vehicle, Mechanical, and Electrical Engineering (...

Table of Contents: “…Simulation and Study on Ride Comfort of Articulated Dump Truck Based on Rigid-Flex CouplingThe Hall Automotive Wheel Speed Sensor and Simulation for its Signal Processing; Wind-Induced Vibration of the Rear-View Mirrors of Car at High Speed; Research on the Affection of Vehicle Lateral Stability Related to the Improved ABS; The Quantification Research of Engine Body Defect that Tested by Ultrasonic Phased Array; Analysis of Vehicle Interior Low-Frequency Noise Based on ATV; The Engine Oil Sump Radiated Noise Optimization Design; A Novel OFDM Radar Algorithm in Vehicular Environment…”
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Biomechanics : optimization, uncertainties and reliability by Kharmanda, Ghias, El Hami, Abdelkhalak

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Advances in applied mechanics and materials : selected, peer reviewed papers from the International Conference on Mechanical Engineering (ICOME 2013), September 19-21, 2013, Matara...

Table of Contents: “…An Experimental Study on the Vertical Flow Past a Finite-Length Horizontal Cylinder at Low Reynolds NumbersEffect of Air Conditioning Position on Thermal Comfort in the Floor Air Conditioning System; Computational Fluid Dynamic Using Parallel Loop of Multi-Cores Processor; Experimental Studies on a Solar Air Heater Having V-Corrugated Absorber Plate with Obstacles Bent Vertically; Energy Savings in Air Conditioning System Using Ejector: An Overview; Empirical Correlations for Sizing Adiabatic Capillary Tube Using LPG as Refrigerant in Split-Type Air-Conditioner.…”
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Pattern recognition : a quality of data perspective by Homenda, Władysław, Pedrycz, Witold, 1953-

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Stochastic modelling of electricity and related markets by Benth, Fred Espen, 1969-

Table of Contents: “…Modelling the dynamics of temperature. 10.3. Empirical analysis of Stockholm temperature dynamics. 10.4. …”
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Extreme events : observations, modeling, and economics

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