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Generative image modeling techniques such as GAN demonstrate highly convincing image generation result. However, user interaction is often necessary to obtain the desired results. Existing attempts add interactivity but require either…

Graphics · Computer Science 2020-09-01 Toby Chong Long Hin , I-Chao Shen , Issei Sato , Takeo Igarashi

The design of multiple experiments is commonly undertaken via suboptimal strategies, such as batch (open-loop) design that omits feedback or greedy (myopic) design that does not account for future effects. This paper introduces new…

Methodology · Statistics 2016-04-29 Xun Huan , Youssef M. Marzouk

We explore computational approaches for visual guidance to aid in creating aesthetically pleasing art and graphic design. Our work complements and builds on previous work that developed models for how humans look at images. Our approach…

Computer Vision and Pattern Recognition · Computer Science 2021-07-14 Qingyuan Zheng , Zhuoru Li , Adam Bargteil

We propose a general methodology of sequential locally optimal design of experiments for explicit or implicit nonlinear models, as they abound in chemical engineering and, in particular, in vapor-liquid equilibrium modeling. As a sequential…

Optimization and Control · Mathematics 2024-03-15 Martin Bubel , Jochen Schmid , Volodymyr Kozachynskyi , Erik Esche , Michael Bortz

In pattern mining, sequential rules provide a formal framework to capture the temporal relationships and inferential dependencies between items. However, the discovery process is computationally intensive. To obtain mining results…

Databases · Computer Science 2026-02-20 Wensheng Gan , Gengsen Huang , Junyu Ren , Philip S. Yu

Designers reportedly struggle with design optimization tasks where they are asked to find a combination of design parameters that maximizes a given set of objectives. In HCI, design optimization problems are often exceedingly complex,…

Human-Computer Interaction · Computer Science 2022-04-19 Liwei Chan , Yi-Chi Liao , George B. Mo , John J. Dudley , Chun-Lien Cheng , Per Ola Kristensson , Antti Oulasvirta

We propose an algorithm for Bayesian functional optimisation - that is, finding the function to optimise a process - guided by experimenter beliefs and intuitions regarding the expected characteristics (length-scale, smoothness, cyclicity…

Machine Learning · Computer Science 2020-09-09 Alistair Shilton , Sunil Gupta , Santu Rana , Svetha Venkatesh

A sequential design problem for rank aggregation is commonly encountered in psychology, politics, marketing, sports, etc. In this problem, a decision maker is responsible for ranking $K$ items by sequentially collecting pairwise noisy…

Methodology · Statistics 2017-10-18 Xi Chen , Yunxiao Chen , Xiaoou Li

The trip planning query searches for preferred routes starting from a given point through multiple Point-of-Interests (PoI) that match user requirements. Although previous studies have investigated trip planning queries, they lack…

Databases · Computer Science 2020-09-09 Yuya Sasaki , Yoshiharu Ishikawa , Yasuhiro Fujiwara , Makoto Onizuka

The challenge of balancing user relevance and content diversity in recommender systems is increasingly critical amid growing concerns about content homogeneity and reduced user engagement. In this work, we propose a novel framework that…

Information Retrieval · Computer Science 2025-06-30 Hiba Bederina , Jill-Jênn Vie

Simulation models of critical systems often have parameters that need to be calibrated using observed data. For expensive simulation models, calibration is done using an emulator of the simulation model built on simulation output at…

Methodology · Statistics 2023-08-24 Özge Sürer , Matthew Plumlee , Stefan M. Wild

Sequential search models provide a powerful framework for studying consumer search using rich data that records the sequence of consumer actions taken during the search process. In existing empirical applications, their implementation often…

Econometrics · Economics 2026-05-05 Tinghan Zhang

Inspired by the classical fractional cascading technique, we introduce new techniques to speed up the following type of iterated search in 3D: The input is a graph $\mathbf{G}$ with bounded degree together with a set $H_v$ of 3D hyperplanes…

Computational Geometry · Computer Science 2025-04-11 Peyman Afshani , Yakov Nekrich , Frank Staals

Designers rely on visual search to explore and develop ideas in early design stages. However, designers can struggle to identify suitable text queries to initiate a search or to discover images for similarity-based search that can…

Human-Computer Interaction · Computer Science 2024-03-05 Kihoon Son , DaEun Choi , Tae Soo Kim , Young-Ho Kim , Juho Kim

While generative modeling has become prevalent across numerous research fields, its integration into the realm of image retrieval remains largely unexplored and underjustified. In this paper, we present a novel methodology, reframing image…

Computer Vision and Pattern Recognition · Computer Science 2024-07-25 Yidan Zhang , Ting Zhang , Dong Chen , Yujing Wang , Qi Chen , Xing Xie , Hao Sun , Weiwei Deng , Qi Zhang , Fan Yang , Mao Yang , Qingmin Liao , Jingdong Wang , Baining Guo

Sequential design is a highly active field of research in active learning which provides a general framework for designing computer experiments with limited computational budgets. It aims to create efficient surrogate models to replace…

Methodology · Statistics 2025-01-03 Paul Lartaud , Philippe Humbert , Josselin Garnier

We propose and analyze sequential design methods for the problem of ranking several response surfaces. Namely, given $L \ge 2$ response surfaces over a continuous input space $\cal X$, the aim is to efficiently find the index of the minimal…

Machine Learning · Statistics 2017-10-17 Ruimeng Hu , Mike Ludkovski

Designing a visualization is often a process of iterative refinement where the designer improves a chart over time by adding features, improving encodings, and fixing mistakes. However, effective design requires external critique and…

Human-Computer Interaction · Computer Science 2023-03-14 Sungbok Shin , Sanghyun Hong , Niklas Elmqvist

Bayesian experimental design (BED) is a framework that uses statistical models and decision making under uncertainty to optimise the cost and performance of a scientific experiment. Sequential BED, as opposed to static BED, considers the…

Machine Learning · Statistics 2020-03-23 Steven Kleinegesse , Christopher Drovandi , Michael U. Gutmann

Nowadays stock photo agencies often have millions of images. Non-stop viewing of 20 million images at a speed of 10 images per second would take more than three weeks. This demonstrates the impossibility to inspect all images and the…

Multimedia · Computer Science 2019-10-15 Kai Uwe Barthel , Nico Hezel , Konstantin Schall , Klaus Jung
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