Decision Making with Limited Data

This thesis studies different approaches to decision making with limited data. First, we study the effects of approximate inference on Thompson sampling in the k-armed bandit problems. Thompson sampling is a successful algorithm but requires posterior inference, which often must be approximated in practice. We show that even small constant inference error (in alpha-divergence) can lead to poor performance (linear regret) due to under-exploration (for alpha \u3c 1) or over-exploration (for alpha \u3e 0) by the approximation. While for alpha \u3e 0 this is unavoidable, for alpha \u3c= 0 the regret can be improved by adding a small amount of forced exploration. Second, we consider the problem of designing a randomized experiment on a source population to estimate the Average Treatment Effect (ATE) on a target population. We propose a novel approach which explicitly considers the target when designing the experiment on the source. Under the covariate shift assumption, we design an unbiased importance-weighted estimator for the target population’s ATE. To reduce the variance of our estimator, we design a covariate balance condition (Target Balance) between the treatment and control groups based on the target population. We show that Target Balance achieves a higher variance reduction asymptotically than methods that do not consider the target during the design phase. Our experiments illustrate that Target Balance reduces the variance even for small sample sizes. Finally, we examine confidence intervals. Historically, mean bounds for small sample sizes fall into 2 categories: methods with unrealistic assumptions about the unknown distribution (e.g., Gaussianity) and methods like Hoeffding\u27s inequality that use weaker assumptions but produce much looser intervals. In 1969, Anderson (1969) proposed a mean confidence interval strictly better than or equal to Hoeffding\u27s whose only assumption is that the distribution\u27s support is contained in an interval [a,b]. For the first time since then, we present a new family of upper bounds that compares favorably to Anderson\u27s. We prove that each bound in the family holds with probability at least 1-alpha for all distributions on an interval [a,b]. Furthermore, one of the bounds is tighter than or equal to Anderson\u27s for all samples

SWOT ANALYSIS AND PROPOSALS TO IMPROVE THE DEVELOPMENT FOR TRAINING YOUNG TAEKWONDO ATHLETES IN VIETNAM

Based on a research of the theory to practice in training, coaching the young athletes generation and in particular Taekwondo, we have carried out a SWOT analysis (Strengths-Weaknesses-Opportunities-Challenge) in the training young athletes of Vietnam Taekwondo in the current period, and outlined a number of measures appropriate solutions to contribute to development in the right direction for the training young athletes to meet recruitment goals and competition of the higher levels (national team).  Article visualizations

Thermodynamics for Trajectories of a Mass Point

On the basis of information theory, a new formalism of classical non-relativistic mechanics of a mass point is proposed. The particle trajectories of a general dynamical system defined on an (1+n)-dimensional smooth manifold are treated geometrically as dynamical variables. Statistical mechanics of particle trajectories are constructed in a classical manner. Thermodynamic variables are introduced through a partition function based on a canonical ensemble of trajectories. Within this theoretical framework, classical mechanics can be interpreted as an equilibrium state of statistical mechanics. The relationships between classical and quantum mechanics are discussed from this statistical mechanical viewpoint. The maximum entropy principle is shown to provide a unified view of both classical and quantum mechanics.Comment: 22 pages, 1 figur

Chiral phospha[n]ferrocenophanes: New Metallopolymers through Ring-Opening Polymerizations

Chiral polymers have many important applications, including separation of racemic compounds and catalysts in asymmetric syntheses. There are many examples of chiral natural polymers, such as proteins, DNA, or cellulose. However, synthetic chiral polymers are rather rare. On the other hand, the incorporation of metal centers into synthetic polymer chains allows the preparation of new functional materials with unique properties that complement those of organic macromolecular materials. Recently, Müller’s group developed a synthetic route to strained ferrocenophanes (FCPs) with planar chirality, and via ring-opening polymerization (ROP), new chiral metallopolymers could be obtained. In this thesis, the syntheses of new chiral phospha[n]FCPs are described, as well as their behaviors towards ROP. New enantiomerically pure phospha[n]FCPs (n = 1, 2) equipped with two iPr groups in α positions were prepared. The molecular structure of diphospha[2]FCP (Sp,Sp,R,R)-90CH2SiMe3 was determined by single-crystal X-ray analysis showing a tilt angle α = 12.2°. Furthermore, the new chiral (Sp,Sp,S,S)-1,1′-(NiPr2)2fciPr 88NiPr2 (fciPr = (Sp,Sp)-[(Me2CH)–(C5H3)]2Fe) was also selectively synthesized and isolated, which gave suitable crystals for single-crystal X-ray analysis. Attempted anionic ROPs were performed on phospha[1]FCPs, however, no polymeric materials could be obtained from these reactions. Detailed studies on phospha[1]FCPs with different substituents on phosphorus atom were carried out, showing that the initiation step in the anionic ROP worked, but the ring-propagation did not occur. In attempts to perform this type of reaction, one of the phospha[1]FCP (Sp,Sp)-20Ph showed the ability to be cleanly ring-opened when using 1 equiv of nBuLi and afforded a 3 to 1 diastereomeric mixture of products. This mixture was sulfurized and a single isomer, (Sp,R)-95S, was isolated and characterized by single-crystal X-ray analysis. In addition, based on the clean anionic ring-opening reaction of the compound (Sp,Sp)-20Ph with 1 equiv of nBuLi, the new chiral ferrocene-based phosphine ligand (Sp,S)-99 was successfully synthesized. In order to measure the amount of strain in [1]FCPs, differential scanning calorimetry (DSC) studies were performed on a series of phospha[1]FCPs having different substituent groups. On the other hand, thermal ROP of compound (Sp,Sp)-21Ph afforded both linear polymer 102n and cyclic oligomers 103. Gel permeation chromatography (GPC) of the sulfurized polymer resulted in a molecular weight of 19 kDa (Mw) and a dispersity of 1.3 (Ð). Mass spectroscopic analysis of the oligomers showed the presence of cyclic species from dimers to hexamers. After sulfurization, preparative thin layer chromatography (PTLC) led to the separation of five isomeric dimers. Structural characterization of one of the dimers (syn-C2-103S-3) by single-crystal X-ray analysis revealed that Fe–Cp bond broke during the thermal ROP process

THE MANAGEMENT OF SPORTS RESOURCES IN HOCHIMINH NATIONAL UNIVERSITY, VIETNAM

Governance plays a very important role in most social organizations. For any organization, company, or a country, a community, the role of governance becomes more important than ever. For schools, the term management is somewhat strange to some people, especially the term “sports management”, which attracts little interest from the leadership. But sport in school is also one of the school's organizations to meet the goal of comprehensive human education. Therefore, the organization of the school requires good governance and management, which is considered to be an essential part to the success of education. Good governance will help the physical training and sport activities to improve the quality of physical training and sports, enhance the movement of physical training and sports activities and especially find the sports talent for the country.  Article visualizations

XRand: Differentially Private Defense against Explanation-Guided Attacks

Recent development in the field of explainable artificial intelligence (XAI) has helped improve trust in Machine-Learning-as-a-Service (MLaaS) systems, in which an explanation is provided together with the model prediction in response to each query. However, XAI also opens a door for adversaries to gain insights into the black-box models in MLaaS, thereby making the models more vulnerable to several attacks. For example, feature-based explanations (e.g., SHAP) could expose the top important features that a black-box model focuses on. Such disclosure has been exploited to craft effective backdoor triggers against malware classifiers. To address this trade-off, we introduce a new concept of achieving local differential privacy (LDP) in the explanations, and from that we establish a defense, called XRand, against such attacks. We show that our mechanism restricts the information that the adversary can learn about the top important features, while maintaining the faithfulness of the explanations.Comment: To be published at AAAI 202