298 citations · 359 across the 8 of their papers we have counts for
9 papers
Model-Agnostic Online Certificate-Driven Calibration for Time Series Forecasting Under Distribution Shift
Chenfeng Huang, Zixuan Ma, George Michailidis
Time series out-of-distribution generalization requires forecasters to remain reliable when deployment dynamics differ from training conditions due to covariate shift, concept shif…
Causal Bayesian Optimization: Foundations, Methods, and Applications
Chenfeng Huang, Thuy T. Le, Zixuan Ma +1
Causal Bayesian Optimization (CBO) combines causal inference with Bayesian optimization to enable sample-efficient intervention selection in systems with causal structure. This sur…
Effective Series Decomposition and Components Learning for Time Series Generation
Zixuan Ma, Chenfeng Huang
Time series generation focuses on modeling the underlying data distribution and resampling to produce authentic time series data. Key components, such as trend and seasonality, dri…
PowerFusion: A Tensor Compiler with Explicit Data Movement Description and Instruction-level Graph IR
Zixuan Ma, Haojie Wang, Jingze Xing +7
Deep neural networks (DNNs) are of critical use in different domains. To accelerate DNN computation, tensor compilers are proposed to generate efficient code on different domain-sp…
GLM-130B: An Open Bilingual Pre-trained Model
Aohan Zeng, Xiao Liu, Zhengxiao Du +15
We introduce GLM-130B, a bilingual (English and Chinese) pre-trained language model with 130 billion parameters. It is an attempt to open-source a 100B-scale model at least as good…
OLLIE: Derivation-based Tensor Program Optimizer
Liyan Zheng, Haojie Wang, Jidong Zhai +7
Boosting the runtime performance of deep neural networks (DNNs) is critical due to their wide adoption in real-world tasks. Existing approaches to optimizing the tensor algebra exp…
A Roadmap for Big Model
Sha Yuan, Hanyu Zhao, Shuai Zhao +97
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm. Researchers have achieved various outcomes in the c…
RisGraph: A Real-Time Streaming System for Evolving Graphs to Support Sub-millisecond Per-update Analysis at Millions Ops/s
Guanyu Feng, Zixuan Ma, Daixuan Li +4
Evolving graphs in the real world are large-scale and constantly changing, as hundreds of thousands of updates may come every second. Monotonic algorithms such as Reachability and…
Ancient Painting to Natural Image: A New Solution for Painting Processing
Tingting Qiao, Weijing Zhang, Miao Zhang +2
Collecting a large-scale and well-annotated dataset for image processing has become a common practice in computer vision. However, in the ancient painting area, this task is not pr…