Search Results for author:
Found 8 papers, 3 papers with code
Diverse and Tailored Image Generation for Zero-shot Multi-label Classification
Our approach introduces a novel image generation framework that produces multi-label synthetic images of unseen classes for classifier training.
Duet: efficient and scalable hybriD neUral rElation undersTanding
Although both data-driven and hybrid methods are proposed to avoid this problem, most of them suffer from high training and estimation costs, limited scalability, instability, and long-tail distribution problems on high-dimensional tables, which seriously affects the practical application of learned cardinality estimators.
Positive Label Is All You Need for Multi-Label Classification
Our paper addresses label noise in MLC by introducing a positive and unlabeled multi-label classification (PU-MLC) method.
TENSILE: A Tensor granularity dynamic GPU memory scheduling method toward multiple dynamic workloads system
In this paper, we demonstrated TENSILE, a method of managing GPU memory in tensor granularity to reduce the GPU memory peak, considering the multiple dynamic workloads.
A parallel-network continuous quantitative trading model with GARCH and PPO
It is a difficult task for both professional investors and individual traders continuously making profit in stock market.
Auto-STGCN: Autonomous Spatial-Temporal Graph Convolutional Network Search Based on Reinforcement Learning and Existing Research Results
In recent years, many spatial-temporal graph convolutional network (STGCN) models are proposed to deal with the spatial-temporal network data forecasting problem.
ConsciousControlFlow(CCF): A Demonstration for conscious Artificial Intelligence
In this demo, we present ConsciousControlFlow(CCF), a prototype system to demonstrate conscious Artificial Intelligence (AI).
Automatic Hyper-Parameter Optimization Based on Mapping Discovery from Data to Hyper-Parameters
However, most machine learning algorithms are sensitive to the hyper-parameters.
