Picture for Yuxin Chen

Yuxin Chen

Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts

Add code
Jul 05, 2024
Figure 1 for Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts
Figure 2 for Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts
Figure 3 for Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts
Figure 4 for Leveraging Data Mining, Active Learning, and Domain Adaptation in a Multi-Stage, Machine Learning-Driven Approach for the Efficient Discovery of Advanced Acidic Oxygen Evolution Electrocatalysts
Viaarxiv icon

Advancing Cross-domain Discriminability in Continual Learning of Vison-Language Models

Add code
Jun 27, 2024
Figure 1 for Advancing Cross-domain Discriminability in Continual Learning of Vison-Language Models
Figure 2 for Advancing Cross-domain Discriminability in Continual Learning of Vison-Language Models
Figure 3 for Advancing Cross-domain Discriminability in Continual Learning of Vison-Language Models
Figure 4 for Advancing Cross-domain Discriminability in Continual Learning of Vison-Language Models
Viaarxiv icon

MEReQ: Max-Ent Residual-Q Inverse RL for Sample-Efficient Alignment from Intervention

Add code
Jun 24, 2024
Viaarxiv icon

On Softmax Direct Preference Optimization for Recommendation

Add code
Jun 14, 2024
Figure 1 for On Softmax Direct Preference Optimization for Recommendation
Figure 2 for On Softmax Direct Preference Optimization for Recommendation
Figure 3 for On Softmax Direct Preference Optimization for Recommendation
Figure 4 for On Softmax Direct Preference Optimization for Recommendation
Viaarxiv icon

No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes

Add code
May 14, 2024
Figure 1 for No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes
Figure 2 for No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes
Figure 3 for No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes
Figure 4 for No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes
Viaarxiv icon

Horizon-Free Regret for Linear Markov Decision Processes

Add code
Mar 15, 2024
Viaarxiv icon

Wukong: Towards a Scaling Law for Large-Scale Recommendation

Add code
Mar 08, 2024
Figure 1 for Wukong: Towards a Scaling Law for Large-Scale Recommendation
Figure 2 for Wukong: Towards a Scaling Law for Large-Scale Recommendation
Figure 3 for Wukong: Towards a Scaling Law for Large-Scale Recommendation
Figure 4 for Wukong: Towards a Scaling Law for Large-Scale Recommendation
Viaarxiv icon

Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation

Add code
Mar 07, 2024
Figure 1 for Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation
Figure 2 for Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation
Figure 3 for Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation
Figure 4 for Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation
Viaarxiv icon

Accelerating Convergence of Score-Based Diffusion Models, Provably

Add code
Mar 06, 2024
Viaarxiv icon

Direct Acquisition Optimization for Low-Budget Active Learning

Add code
Feb 08, 2024
Figure 1 for Direct Acquisition Optimization for Low-Budget Active Learning
Figure 2 for Direct Acquisition Optimization for Low-Budget Active Learning
Figure 3 for Direct Acquisition Optimization for Low-Budget Active Learning
Figure 4 for Direct Acquisition Optimization for Low-Budget Active Learning
Viaarxiv icon