Search Results for author:
Found 4 papers, 3 papers with code
BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
This reformulation enables the use of first-order optimization algorithms in calculating the backward pass gradients, allowing our framework to potentially utilize any state-of-the-art solver.
MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Generative models aim to simulate realistic effects of various actions across different contexts, from text generation to visual effects.
HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information
To overcome the shortcomings of previous work, we proposed a novel stock trend forecasting framework that can adequately mine the concept-oriented shared information from predefined concepts and hidden concepts.
Temporally Correlated Task Scheduling for Sequence Learning
In many applications, a sequence learning task is usually associated with multiple temporally correlated auxiliary tasks, which are different in terms of how much input information to use or which future step to predict.
