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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Prediction When Factors are Weak
因素较弱 预测 宏观经济预测
2023/5/5
In macroeconomic forecasting, principal component analysis (PCA) has been the most prevalent approach to the recovery of factors, which summarize information in a large set of macro predictors. Nevert...
Integrative approaches for microRNA target prediction: combining sequence information and the paired mRNA and miRNA expression profiles
target prediction expression profile integrative analysis
2016/1/20
Gene regulation is a key factor in gaining a full understanding of molecular biology. microRNA (miRNA), a novel class of non-coding RNA, has recently been found to be one crucial class of post-transac...
Efficient Prediction Designs for Random Fields
optimal design pareto front empirical kriging gaussian process models
2013/6/14
For estimation and predictions of random fields it is increasingly acknowledged that the kriging variance may be a poor representative of true uncertainty. Experimental designs based on more elaborate...
Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families
SNML Exchangeability Exponential Family Online Learning Logarithmic Loss Bayesian Strategy Jeffreys Prior Fisher Information
2013/6/17
We study online learning under logarithmic loss with regular parametric models. Hedayati and Bartlett (2012b) showed that a Bayesian prediction strategy with Jeffreys prior and sequential normalized m...
Learning Policies for Contextual Submodular Prediction
Learning Policies Contextual Submodular Prediction
2013/6/14
Many prediction domains, such as ad placement, recommendation, trajectory prediction, and document summarization, require predicting a set or list of options. Such lists are often evaluated using subm...
Heart Disease Prediction System using Associative Classification and Genetic Algorithm
Andhra Pradesh Associative classification Genetic algorithm Gini Index Z-Statistics
2013/5/2
Associative classification is a recent and rewarding technique which integrates association rule mining and classification to a model for prediction and achieves maximum accuracy. Associative classifi...
K-Nearest Neighbour algorithm coupled with logistic regression in medical case-based reasoning systems. Application to prediction of access to the renal transplant waiting list in Brittany
Case-based Reasoning systems logistic models similarity measures k-nearest neighbors algorithms classi-fication
2013/4/28
Introduction. Case Based Reasoning (CBR) is an emerg- ing decision making paradigm in medical research where new cases are solved relying on previously solved similar cases. Usually, a database of sol...
Shrinkage estimators for prediction out-of-sample: Conditional performance
James-Stein estimator rando mmatrix theory random design
2012/11/22
We find that, in a linear model, the James-Stein estimator, which dominates the maximum-likelihood estimator in terms of its in-sample prediction error, can perform poorly compared to the maximum-like...
Minimax Policies for Combinatorial Prediction Games
Minimax Policies Combinatorial Prediction Games
2011/6/20
We address the online linear optimization problem when the actions of the forecaster are represented by
binary vectors. Our goal is to understand the magnitude of the minimax regret for the worst pos...
An Introduction to Artificial Prediction Markets for Classification
online learning supervised learning random forest implicit online learning
2011/3/18
Prediction markets are used in real life to predict outcomes of interest such as presidential elections. This paper presents a mathematical theory of artificial prediction markets for supervised learn...
No-Regret Reductions for Imitation Learning and Structured Prediction
No-Regret Reductions for Imitation Learning Structured Prediction
2010/11/9
Sequential prediction problems such as imitation learning, where future observations depend on
previous predictions (actions), violate the common i.i.d. assumptions made in statistical learning.
Online Multiple Kernel Learning for Structured Prediction
Online Multiple Kernel Learning r Structured Prediction
2010/10/19
Despite the recent progress towards efficient multiple kernel learning (MKL), the structured output case remains an open research front. Current approaches involve repeatedly solving a batch learning...
Prediction and variable selection with the adaptive Lasso
adaptive Lasso prediction restricted eigenvalue thresholding variable selection
2010/3/9
We revisit the adaptive Lasso in a high-dimensional linear model,
and provide bounds for its prediction error and for its number of false positive
selections. We compare the adaptive Lasso with an “...
Robust quantile estimation and prediction for spatial processes
Spatial processes Kernel estimate Conditional quantile Spatial prediction
2010/3/9
In this paper, we present a statistical framework for modeling conditional quantiles of spatial processes
assumed to be strongly mixing in space. We establish the L1 consistency and the asymptotic no...
A Monte Carlo Algorithm for Universally Optimal Bayesian Sequence Prediction and Planning
recurrent neural network Turing machine AIXI reinforcement learning planning sequence prediction Universal prior
2010/3/9
The aim of this work is to address the question of whether we can in principle
design rational decision-making agents or artificial intelligences embedded
in computable physics such that their decis...