17 citations · 18 across the 10 of their papers we have counts for
4 papers · 1 filter
DDTime: Dataset Distillation with Spectral Alignment and Information Bottleneck for Time-Series Forecasting
Yuqi Li, Kuiye Ding, Chuanguang Yang +5
Time-series forecasting is fundamental across many domains, yet training accurate models often requires large-scale datasets and substantial computational resources. Dataset distil…
QKCV Attention: Enhancing Time Series Forecasting with Static Categorical Embeddings for Both Lightweight and Pre-trained Foundation Models
Hao Wang, Baojun Ma
In real-world time series forecasting tasks, category information plays a pivotal role in capturing inherent data patterns. This paper introduces QKCV (Query-Key-Category-Value) at…
Enhancing Vector Quantization with Distributional Matching: A Theoretical and Empirical Study
Xianghong Fang, Litao Guo, Hengchao Chen +8
The success of autoregressive models largely depends on the effectiveness of vector quantization, a technique that discretizes continuous features by mapping them to the nearest co…
Simplifying Bayesian Optimization Via In-Context Direct Optimum Sampling
Gustavo Sutter Pessurno de Carvalho, Mohammed Abdulrahman, Hao Wang +7
The optimization of expensive black-box functions is ubiquitous in science and engineering. A common solution to this problem is Bayesian optimization (BO), which is generally comp…