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Convolutional Neural Networks (CNNs) have been the state of the art in many applications, including computer vision and multimedia forensics. Translation invariance is often included among the reasons for their success. However, the recent literature has ...

The inherently time-dependent dynamics which underly the neuronal spiking communication, are ubquitous throughout brain, and yet are not fully understood. Likewise time-based mechanisms are underdeveloped in the field of Machine and Reinforcement ...

Nowadays, contrastive self-supervised learning has been widely incorporated into sequential recommender systems. However, most existing contrastive sequential recommender systems simply emphasize the overall information of interaction sequences, thereby ...

The current article explores the affects of space-time discrete stochastic competitive neural networks. In line with a discrete-space and discrete-time constant variation formula, boundedness and stability are addressed to the space-time discrete ...

Time series forecasting is a critical and challenging problem in many real applications. Recently, Transformer-based models prevail in time series forecasting due to their advancement in long-range dependencies learning. Besides, some models introduce ...

E-commerce business is revolutionizing our shopping experiences by providing convenient and straightforward services. One of the most fundamental problems is how to balance the demand and supply in market segments to build an efficient platform. While ...

Behavior tracing or predicting is a key component in various application scenarios like online user modeling and ubiquitous computing, which significantly benefits the system design (e.g., resource pre-caching) and improves the user experience (e.g., ...

With the ever-growing need of data in HPC applications, the congestion at the I/O level becomes critical in supercomputers. Architectural enhancement such as burst buffers and pre-fetching are added to machines but are not sufficient to prevent ...

Spatial-temporal prediction is a fundamental problem for constructing smart city, which is useful for tasks such as traffic control, taxi dispatching, and environment policy making. Due to data collection mechanism, it is common to see data collection ...

Quantum walks determined by the coin operator on graphs have been intensively studied. The typical examples of coin operator are the Grover and Fourier matrices. The periodicity of the Grover walk is well investigated. However, the corresponding result ...

The traditional scrambling technology based on the low-dimensional Arnold transformation (AT) is not able to assure the security of images during the transmission process, since the key space of the low-dimensional AT is small and the scrambling period is ...

Stop-and-move is a popular mobility pattern describing the behavior of an object alternating periods of relative stationarity (stops) with periods of mobility (move). In this demo, we present a system supporting the discovery of periodic stops in ...

Our internal experience of time reflects what is going in the world around us. Our body»s natural rhythms get disrupted for a variety of external factors, including exposure to collective events. We collect readings of steps, sleep, and heart rates from ...

Periodic phenomena are ubiquitous, but detecting and predicting periodic events can be difficult in noisy environments. We describe a model of periodic events that covers both idealized and realistic scenarios characterized by multiple kinds of noise. ...

Personal sensors are now ubiquitous and they can be wearable, they can be carried or they can be in situ and fixed into our homes or workplaces. The major factors influencing the growth in personal sensing include that they are smaller, smarter, cheaper,...

Nowadays, billions of people use the Web in connection with their daily needs. A significant part of these needs are constituted by search tasks that are usually addressed by search engines. Thus, daily search needs result in regular user engagement ...

Modeling and predicting the popularity dynamics of individual user generated items on online social networks has important implications in a wide range of areas. The challenge of this problem comes from the inequality of the popularity of content and ...

This paper introduces a new way to analyse and visualize quantified-self or lifelog data captured from any lifelogging device over an extended period of time. The mechanism works on the raw, unstructured lifelog data by detecting periodicities, those ...

Modern Internet companies improve evaluation criteria of their data-driven decision-making that is based on online controlled experiments (also known as A/B tests). The amplitude metrics of user engagement are known to be well sensitive to service ...

Nowadays, billions of people use the Web in connection with their daily needs. A significant part of the needs are constituted by search tasks that are usually addressed by search engines. Thus, daily search needs result in regular user engagement with ...