Optimization

CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling ICLR 2024 Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment NeurIPS 2024 CALE: Continuous Arcade Learning Environment NeurIPS 2024 Calibration Bottleneck: Over-compressed Representations are Less Calibratable ICML 2024 Can Gaussian Sketching Converge Faster on a Preconditioned Landscape? ICML 2024 Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach NeurIPS 2024 Can't Be Late: Optimizing Spot Instance Savings under Deadlines NSDI 2024 Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective ICML 2024 Cardinality-Aware Set Prediction and Top-k Classification NeurIPS 2024 Careful with that Scalpel: Improving Gradient Surgery with an EMA ICML 2024 Cascade Speculative Drafting for Even Faster LLM Inference NeurIPS 2024 Categorical Flow Matching on Statistical Manifolds NeurIPS 2024 Causal Bandits with General Causal Models and Interventions AISTATS 2024 Causality-enhanced Discreted Physics-informed Neural Networks for Predicting Evolutionary Equations IJCAI 2024 Causal Optimal Transport of Abstractions CLeaR 2024 Causal Q-Aggregation for CATE Model Selection AISTATS 2024 CcDPM: A Continuous Conditional Diffusion Probabilistic Model for Inverse Design AAAI 2024 CeeBERT: Cross-Domain Inference in Early Exit BERT ACL 2024 CEGAR-Based Approach for Solving Combinatorial Optimization Modulo Quantified Linear Arithmetics Problems AAAI 2024 CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework NeurIPS 2024 Centralized Selection with Preferences in the Presence of Biases ICML 2024 Centroid-Based Efficient Minimum Bayes Risk Decoding ACL 2024 CERT-ED: Certifiably Robust Text Classification for Edit Distance EMNLP 2024 Certified Machine Unlearning via Noisy Stochastic Gradient Descent NeurIPS 2024 CF-NeRF: Camera Parameter Free Neural Radiance Fields with Incremental Learning AAAI 2024