heterogeneous data
Heterogeneous data refers to diverse types of data that can come from different sources, formats, or modalities. In AI, utilizing heterogeneous data can enhance model robustness and improve performance across tasks.
- Adaptive LoRA Experts Allocation and Selection for Federated Fine-Tuning
- Learning Reconfigurable Representations for Multimodal Federated Learning with Missing Data
- MTBBench: A Multimodal Sequential Clinical Decision-Making Benchmark in Oncology
- Position: Biology is the Challenge Physics-Informed ML Needs to Evolve
- Rising from Ashes: Generalized Federated Learning via Dynamic Parameter Reset
- Second-Order Convergence in Private Stochastic Non-Convex Optimization
- TabDPT: Scaling Tabular Foundation Models on Real Data
- TrajAgent: An LLM-Agent Framework for Trajectory Modeling via Large-and-Small Model Collaboration