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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

CAILA: Concept-Aware Intra-Layer Adapters for Compositional Zero-Shot Learning WACV 2024 Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment NeurIPS 2024 CALE: Continuous Arcade Learning Environment NeurIPS 2024 Calibrating LLM-Based Evaluator COLING 2024 Calibrating Long-form Generations From Large Language Models EMNLP 2024 Calibration Bottleneck: Over-compressed Representations are Less Calibratable ICML 2024 Can Biases in ImageNet Models Explain Generalization? CVPR 2024 Can CLIP Count Stars? An Empirical Study on Quantity Bias in CLIP EMNLP 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 Humans Identify Domains? COLING 2024 Can Implicit Bias Imply Adversarial Robustness? ICML 2024 Can Large Language Models Always Solve Easy Problems if They Can Solve Harder Ones? EMNLP 2024 Can Large Language Models Learn Independent Causal Mechanisms? EMNLP 2024 Can Learned Optimization Make Reinforcement Learning Less Difficult? NeurIPS 2024 Can LLMs Learn from Previous Mistakes? Investigating LLMs’ Errors to Boost for Reasoning ACL 2024 Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning? ICML 2024 Can Modelling Inter-Rater Ambiguity Lead To Noise-Robust Continuous Emotion Predictions? Interspeech 2024 Can Small Language Models Help Large Language Models Reason Better?: LM-Guided Chain-of-Thought COLING 2024 Can't Be Late: Optimizing Spot Instance Savings under Deadlines NSDI 2024 Can Transformers Learn n-gram Language Models? EMNLP 2024 Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision? ICLR 2024 Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective ICML 2024 CAP: A Context-Aware Neural Predictor for NAS IJCAI 2024 Capturing the denoising effect of PCA via compression ratio NeurIPS 2024