RTB Formulation Using Point Process

We propose a general stochastic framework for modelling repeated auctions in the Real Time Bidding (RTB) ecosystem using point processes. The flexibility of the framework allows a variety of auction scenarios including configuration of information provided to player, determination of auction winner and quantification of utility gained from each auctions. We propose theoretical results on how this formulation of process can be approximated to a Poisson point process, which enables the analyzer to take advantage of well-established properties. Under this framework, we specify the player's optimal strategy under various scenarios. We also emphasize that it is critical to consider the joint distribution of utility and market condition instead of estimating the marginal distributions independently

Generalized gravity model for human migration

The gravity model (GM) analogous to Newton's law of universal gravitation has successfully described the flow between different spatial regions, such as human migration, traffic flows, international economic trades, etc. This simple but powerful approach relies only on the 'mass' factor represented by the scale of the regions and the 'geometrical' factor represented by the geographical distance. However, when the population has a subpopulation structure distinguished by different attributes, the estimation of the flow solely from the coarse-grained geographical factors in the GM causes the loss of differential geographical information for each attribute. To exploit the full information contained in the geographical information of subpopulation structure, we generalize the GM for population flow by explicitly harnessing the subpopulation properties characterized by both attributes and geography. As a concrete example, we examine the marriage patterns between the bride and the groom clans of Korea in the past. By exploiting more refined geographical and clan information, our generalized GM properly describes the real data, a part of which could not be explained by the conventional GM. Therefore, we would like to emphasize the necessity of using our generalized version of the GM, when the information on such nongeographical subpopulation structures is available.Comment: 14 pages, 6 figures, 2 table

Addressing Distribution Shift in RTB Markets via Exponential Tilting

Distribution shift in machine learning models can be a primary cause of performance degradation. This paper delves into the characteristics of these shifts, primarily motivated by Real-Time Bidding (RTB) market models. We emphasize the challenges posed by class imbalance and sample selection bias, both potent instigators of distribution shifts. This paper introduces the Exponential Tilt Reweighting Alignment (ExTRA) algorithm, as proposed by Marty et al. (2023), to address distribution shifts in data. The ExTRA method is designed to determine the importance weights on the source data, aiming to minimize the KL divergence between the weighted source and target datasets. A notable advantage of this method is its ability to operate using labeled source data and unlabeled target data. Through simulated real-world data, we investigate the nature of distribution shift and evaluate the applicacy of the proposed model

Development of Optimized Path Planning and Autonomous Control for Return-to-point Vehicle of High Altitude Ballooning

In 2004, The Atmospheric and Space Threshold Research Oklahoma (ASTRO) program was launched to provide access to the near space environment for both educational and research purposes. Mainly, this ASTRO vehicle consisted of four parts: Sounding weather balloon to produce buoy force during the ascent phase, circular parachute to produce drag force during the descent phase, tracking gear with GPS (Global Positioning System) to check the position from the ground, and experimental payloads. The descent phase utilizes a circular parachute, and as such, there are no means of controlling the landing location of the vehicle and payloads. Without control, the direction the parachute takes is dependent upon the winds aloft which can allow payloads to land in undesirable locations, such as rivers, lakes, or the middle of vast forests. At times, the flight must be cancelled before it even begins if the risks of a long or difficult recovery are predicted. As the ASTRO project has evolved, the necessity of control of the payloads over the descent phase has also become obvious. In order to address this need, a study of a Return-to-Point Vehicle (RPV) has been started. Parafoil vehicles which are used for RPVs have proven to be useful in many situations from the previous research. Once the RPV has reached the desired altitude, generally around 100,000 ft, it is released from the balloon. When the RPV has been released, it will follow a trajectory which is programmed on Autopilot to direct it a desired landing zone. Some researchers tried to analyze and test the parafoil, but there are no reported uses of the parafoil for dropping the payload from high altitudes; in addition, there are not commercial products to be matched with the ASTRO research as well. Therefore, the purpose of this research is to design the RPV and to develop the optimal trajectory to satisfy the requirements of the ASTRO project. In this research, the most important objective is to develop a cost-effective, simple, and reliable autopilot system which can be applied to the payload used in the ASTRO project.Mechanical Engineerin