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Advanced statistical methods in data science / / edited by Ding-Geng Chen, Jiahua Chen, Xuewen Lu, Grace Y. Yi, Hao Yu
| Advanced statistical methods in data science / / edited by Ding-Geng Chen, Jiahua Chen, Xuewen Lu, Grace Y. Yi, Hao Yu |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XVI, 222 p. 41 illus., 20 illus. in color.) |
| Disciplina | 519.50285 |
| Collana | ICSA Book Series in Statistics |
| Soggetto topico |
Statistics
Big data Statistical Theory and Methods Big Data/Analytics Statistics for Business, Management, Economics, Finance, Insurance |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I: Data Analysis Based on Latent or Dependent Variable Models -- Chapter 1: A New Method for Robust Mixture Regression and Outlier Detection -- Chapter 2: The Mixture Gatekeeping Procedure Based on Weighted Multiple Testing Correction for Correlated Tests -- Chapter 3: Regularization in Regime-switching Gaussian Autoregressive Models -- Chapter 4: Modeling Zero Inflation and Over-dispersion in the Length of Hospital Stay for Patients with Ischaemic Heart Disease -- Chapter 5: Robust Optimal Interval Design for High-Dimensional Dose Finding in Multi-Agent Combination Trials -- Part II: Life Time Data Analysis -- Chapter 6: Group Selection in Semi-parametric Accelerated Failure Time Model -- Chapter 7: A Proportional Odds Model for Regression Analysis of Case I Interval-Censored Data -- Chapter 8: Empirical Likelihood Inference under Density Ratio Models Based on Type I Censored Samples: Hypothesis Testing and Quantile Estimation -- Chapter 9: Recent Development in the Joint Modeling of Longitudinal Quality of Life Measurements and Survival Data from Cancer Clinical Trials -- Part III: Applied Data Analysis -- Chapter 10: Confidence Weighting Procedures for Multiple Choice Tests -- Chapter 11: Improving the Robustness of Parametric Imputation -- Chapter 12: Maximum Smoothed Likelihood Estimation of the Centre of a Symmetric Distribution -- Chapter 13: Dividend Pay-out Problems with the Logarithmic Utility -- Chapter 14: Modeling the Common Risk among Equities: A Multivariate Time Series Model with an Additive GARCH Structure. |
| Record Nr. | UNINA-9910155548503321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advances in Time Series Methods and Applications : The A. Ian McLeod Festschrift / / edited by Wai Keung Li, David A. Stanford, Hao Yu
| Advances in Time Series Methods and Applications : The A. Ian McLeod Festschrift / / edited by Wai Keung Li, David A. Stanford, Hao Yu |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | New York, NY : , : Springer New York : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (VIII, 293 p. 37 illus., 7 illus. in color.) |
| Disciplina | 330.015195 |
| Collana | Fields Institute Communications |
| Soggetto topico |
Statistics
Statistics in Business, Management, Economics, Finance, Insurance |
| ISBN | 1-4939-6568-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Ian McLeod's Contribution to Time Series Analysis: a Tribute (W.K. Li) -- 2. The Doubly Adaptive LASSO for Vector Autoregressive Models (Z.Z. Liu, R. Kulperger, H. Yu) -- 3. On diagnostic checking autoregressive conditional duration models with wavelet-based spectral density estimators (P. Duchesne, Y. Hong) -- 4. Diagnostic checking for Weibull autoregressive conditional duration models (Y. Zheng, Y. Li, W.K. Li, G. Li) -- 5. Diagnostic checking for Partially Nonstationary Multivariate ARMA Models (M.T. Tai, Y.X. Yang, and S.Q. Ling) -- 6. The portmanteau tests and the LM test for ARMA models with uncorrelated errors (N. Katayama) -- 7. Generalized C(alpha) tests for estimating functions with serial dependence J.-M. Dufour, A. Tognon, P. Tuvaandorj) -- Regression Models for Ordinal Categorical Time Series Data (B.C. Sutradhar, R.P. Rao) -- 9. Identification of Threshold Autoregressive Moving Average Models (Q. Xia, H. Wong) -- 10. Improved Seasonal Mann-Kendall Tests for Trend Analysis in Water Resources Time Series (Y. Zhang, P. Cabilio and K. Nadeem) -- 11. A brief derivation of the asymptotic distribution of Pearson’s statistic and an accurate approximation to its exact distribution (S.B. Provost) -- 12. Business Resilience during Power Shortages: A Power Saving Rate Measured by Power Consumption Time Series in Industrial Sector before and after the Great East Japan Earthquake in 2011 (Y. Kajitani) -- Atmospheric CO2 and global temperatures: the strength and nature of their dependence (G. Tunnicliffe Wilson) -- Catching Uncertainty of Wind: A Blend of Sieve Bootstrap and Regime Switching Models for Probabilistic Short-term Forecasting of Wind Speed (Y.R. Gel, V. Lyubchich, S.E. Ahmed). . |
| Record Nr. | UNINA-9910154846503321 |
| New York, NY : , : Springer New York : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Compact and Fast Machine Learning Accelerator for IoT Devices [[electronic resource] /] / by Hantao Huang, Hao Yu
| Compact and Fast Machine Learning Accelerator for IoT Devices [[electronic resource] /] / by Hantao Huang, Hao Yu |
| Autore | Huang Hantao |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (157 pages) |
| Disciplina | 006.31 |
| Collana | Computer Architecture and Design Methodologies |
| Soggetto topico |
Engineering
Computer science Mathematical optimization Computational Intelligence Processor Architectures Optimization |
| ISBN | 981-13-3323-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Computing on Edge Devices in Internet-of-things (IoT) -- The Rise of Machine Learning in IoT system -- Least-squares-solver for Shadow Neural Network -- Tensor-solver for Deep Neural Network -- Distributed-solver for Networked Neural Network -- Conclusion. |
| Record Nr. | UNINA-9910483157403321 |
Huang Hantao
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| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Emerging Technology and Architecture for Big-data Analytics / / edited by Anupam Chattopadhyay, Chip Hong Chang, Hao Yu
| Emerging Technology and Architecture for Big-data Analytics / / edited by Anupam Chattopadhyay, Chip Hong Chang, Hao Yu |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
| Descrizione fisica | 1 online resource (XI, 330 p. 162 illus., 98 illus. in color.) |
| Disciplina | 621.3815 |
| Soggetto topico |
Electronic circuits
Microprocessors Big data Circuits and Systems Processor Architectures Electronic Circuits and Devices Big Data/Analytics |
| ISBN | 3-319-54840-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Part I State-of-the-Art Architectures and Automation for Data-analytics -- Chapter 1. Scaling the Java Virtual Machine on a Many-core System -- Chapter 2.Scaling the Java Virtual Machine on a Many-core System -- Chapter 3.Least-squares based Machine Learning Accelerator for Big-data Analytics in Smart Buildings -- Chapter 4.Compute-in-memory Architecture for Data-Intensive Kernels -- Chapter 5. New Solutions for Cross-Layer System-Level and High-Level Synthesis -- Part II New Solutions for Cross-Layer System-Level and High-Level Synthesis -- Chapter 6.Side Channel Attacks and Efficient Countermeasures on Residue Number System Multipliers -- Chapter 7. Ultra-Low-Power Biomedical Circuit Design and Optimization: Catching The Don’t Cares -- Chapter 8.Acceleration of MapReduce Framework on a Multicore Processor -- Chapter 9. Adaptive dynamic range compression for improving envelope-based speech perception: Implications for cochlear implants -- Part III Emerging Technology, Circuits and Systems for Data-analytics -- Chapter 10. Emerging Technology, Circuits and Systems for Data-analytics -- Chapter 11. Energy Efficient Spiking Neural Network Design with RRAM Devices -- Chapter 12. Efficient Neuromorphic Systems and Emerging Technologies - Prospects and Perspectives -- Chapter 13. In-memory Data Compression Using ReRAMs -- Chapter 14. In-memory Data Compression Using ReRAMs -- Chapter 15.Data Analytics in Quantum Paradigm – An Introduction. |
| Record Nr. | UNINA-9910254323803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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