How can we efficiently analyze a specific time range on an irregular tensor? PARAFAC2 decomposition is widely used when analyzing an irregular tensor which consists of several matrices with different row sizes. A crucial task related to PARAFAC2 ...

Given an irregular tensor from a newly emerging domain, how can we quickly and accurately capture its patterns utilizing existing irregular tensors in multiple domains? The problem is of great importance for various tasks such as finding patterns of a ...

How can we leverage inherent frequency features of stock signals for effective portfolio optimization? Portfolio optimization in the domain of finance revolves around strategically allocating assets to maximize returns. Recent advancements highlight the ...

Given a multidimensional array, how can we optimize the computation process for a part of Fourier coefficients? Discrete Fourier transform plays an overarching role in various data mining tasks. Recent interest has focused on efficiently calculating a ...

How can we recommend cold-start bundles to users? The cold-start problem in bundle recommendation is crucial because new bundles are continuously created on the Web for various marketing purposes. Despite its importance, existing methods for cold-start ...

How can we accurately transcribe speech signals into texts when only a portion of them are annotated? ASR (Automatic Speech Recognition) systems are extensively utilized in many real-world applications including automatic translation systems and ...

Graphs are widely used for representing pairwise interactions in complex systems. Since such real-world graphs are large and often evergrowing, sampling subgraphs is useful for various purposes, including simulation, visualization, stream processing, ...

How can we efficiently and accurately analyze an irregular tensor in a dual-way streaming setting where the sizes of two dimensions of the tensor increase over time? What types of anomalies are there in the dual-way streaming setting? An irregular ...

How can we accurately identify new memory workloads while classifying known memory workloads? Verifying DRAM (Dynamic Random Access Memory) using various workloads is an important task to guarantee the quality of DRAM. A crucial component in the process ...

When recommending personalized top-k items to users, how can we recommend them diversely while satisfying users’ needs? Aggregately diversified recommender systems aim to recommend a variety of items across whole users without sacrificing the ...

How can we expose diverse items across all users while satisfying their needs in bundle recommendations? Diversified bundle recommendation is a crucial task since it leads to great benefits for both sellers and users. However, there have been no ...$\mathrm{}$$\mathrm{}$

Given a dense tensor, how can we efficiently discover hidden relations and patterns in static and online streaming settings? Tucker decomposition is a fundamental tool to analyze multidimensional arrays in the form of tensors. However, existing Tucker ...

How can we efficiently compress convolutional neural network (CNN) using depthwise separable convolution, while retaining their accuracy on classification tasks? Depthwise separable convolution, which replaces a standard convolution with a ...

How can we accurately recommend actions for users to control their devices at home? Action recommendation for smart home has attracted increasing attention due to its potential impact on the markets of Internet of Things (IoT). However, designing an ...

Given a graph with partial observations of node features, how can we estimate the missing features accurately? Feature estimation is a crucial problem for analyzing real-world graphs whose features are commonly missing during the data collection process. ...

How can we classify graph-structured data only with positive labels? Graph-based positive-unlabeled (PU) learning is to train a binary classifier given only the positive labels when the relationship between examples is given as a graph. The ...

What are the key structures existing in a large real-world MMORPG (Massively Multiplayer Online Role-Playing Game) graph? How can we compactly summarize an MMORPG graph with hierarchical node labels, considering substructures at different levels of ...

Given a graph dataset, how can we augment it for accurate graph classification? Graph augmentation is an essential strategy to improve the performance of graph-based tasks, and has been widely utilized for analyzing web and social graphs. However, ...

Graphs are widely used for representing pairwise interactions in complex systems. Since such real-world graphs are large and often evergrowing, sampling a small representative subgraph is indispensable for various purposes: simulation, visualization, ...

Given a sparse time-evolving tensor, how can we effectively factorize it to accurately discover latent patterns? Tensor decomposition has been extensively utilized for analyzing various multi-dimensional real-world data. However, existing tensor ...