Han-Jia Ye

19

Papers

86

Total Citations

Papers (19)

TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems

Leveraging Cross-Modal Neighbor Representation for Improved CLIP Classification

MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning

Revisiting Nearest Neighbor for Tabular Data: A Deep Tabular Baseline Two Decades Later

Improving LLMs for Recommendation with Out-Of-Vocabulary Tokens

Understanding the Limits of Deep Tabular Methods with Temporal Shift

Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts

Expandable Subspace Ensemble for Pre-Trained Model-Based Class-Incremental Learning

SIN: Selective and Interpretable Normalization for Long-Term Time Series Forecasting

Enhancing Class-Imbalanced Learning with Pre-Trained Guidance through Class-Conditional Knowledge Distillation

Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images

Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning

Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning

Task-Agnostic Guided Feature Expansion for Class-Incremental Learning

External Knowledge Injection for CLIP-Based Class-Incremental Learning

Integrating Task-Specific and Universal Adapters for Pre-Trained Model-based Class-Incremental Learning

MIETT: Multi-Instance Encrypted Traffic Transformer for Encrypted Traffic Classification

Capability Instruction Tuning

Learning Only When It Matters: Cost