Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Ren, Yongli"'
With the rise of Large Language Models (LLMs) such as ChatGPT, researchers have been working on how to utilize the LLMs for better recommendations. However, although LLMs exhibit black-box and probabilistic characteristics (meaning their internal wor
Externí odkaz:
http://arxiv.org/abs/2411.12121
Addressing the challenges of irregularity and concept drift in streaming time series is crucial in real-world predictive modelling. Previous studies in time series continual learning often propose models that require buffering of long sequences, pote
Externí odkaz:
http://arxiv.org/abs/2411.07413
We propose Counterfactual Analysis Quadratic Unconstrained Binary Optimization (CAQUBO) to solve QUBO problems for feature selection in recommender systems. CAQUBO leverages counterfactual analysis to measure the impact of individual features and fea
Externí odkaz:
http://arxiv.org/abs/2410.15272
Using Quantum Computers to solve problems in Recommender Systems that classical computers cannot address is a worthwhile research topic. In this paper, we use Quantum Annealers to address the feature selection problem in recommendation algorithms. Th
Externí odkaz:
http://arxiv.org/abs/2407.02839
In the marked temporal point processes (MTPP), a core problem is to parameterize the conditional joint PDF (probability distribution function) $p^*(m,t)$ for inter-event time $t$ and mark $m$, conditioned on the history. The majority of existing stud
Externí odkaz:
http://arxiv.org/abs/2308.02360
Autor:
Qin, Kyle K., Rahaman, Mohammad S., Ren, Yongli, Cheng, Chi-Tsun, Cole, Ivan, Salim, Flora D.
Human movements in the workspace usually have non-negligible relations with air quality parameters (e.g., CO$_2$, PM2.5, and PM10). We establish a system to monitor indoor human mobility with air quality and assess the interrelationship between these
Externí odkaz:
http://arxiv.org/abs/2306.11773
Sparsity is a common issue in many trajectory datasets, including human mobility data. This issue frequently brings more difficulty to relevant learning tasks, such as trajectory imputation and prediction. Nowadays, little existing work simultaneousl
Externí odkaz:
http://arxiv.org/abs/2301.04482
Ordinary Differential Equations (ODE) based models have become popular as foundation models for solving many time series problems. Combining neural ODEs with traditional RNN models has provided the best representation for irregular time series. Howev
Externí odkaz:
http://arxiv.org/abs/2212.03560
Reconfigurable reflectarray antennas (RRAs) have rapidly developed with various prototypes proposed in recent literatures. However, designing wideband, multiband, or high-frequency RRAs faces great challenges, especially the lengthy simulation time d
Externí odkaz:
http://arxiv.org/abs/2211.08632
Autor:
Khaokaew, Yonchanok, Holcombe-James, Indigo, Rahaman, Mohammad Saiedur, Liono, Jonathan, Trippas, Johanne R., Spina, Damiano, Belkin, Nicholas, Bailey, Peter, Bennett, Paul N., Ren, Yongli, Sanderson, Mark, Scholer, Falk, White, Ryen W., Salim, Flora D.
Digital Assistants (DAs) can support workers in the workplace and beyond. However, target user needs are not fully understood, and the functions that workers would ideally want a DA to support require further study. A richer understanding of worker n
Externí odkaz:
http://arxiv.org/abs/2208.03443