← Learning Types
Machine Learning › Learning Types ›

Supervised Learning

988 directly classified papers

Papers per year

Papers

DeRDaVa: Deletion-Robust Data Valuation for Machine Learning AAAI 2024
Enhancing Training of Spiking Neural Network with Stochastic Latency AAAI 2024
Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation NIPS 2024
SmurfCat at SemEval-2024 Task 6: Leveraging Synthetic Data for Hallucination Detection SEMEVAL 2024
Don’t Blame the Data, Blame the Model: Understanding Noise and Bias When Learning from Subjective Annotations EACL 2024
Which Is More Effective in Label Noise Cleaning, Correction or Filtering? AAAI 2024
MALTO at SemEval-2024 Task 6: Leveraging Synthetic Data for LLM Hallucination Detection SEMEVAL 2024
AIpom at SemEval-2024 Task 8: Detecting AI-produced Outputs in M4 SEMEVAL 2024
Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression NIPS 2024
PEAR at SemEval-2024 Task 1: Pair Encoding with Augmented Re-sampling for Semantic Textual Relatedness SEMEVAL 2024
Deja Vu at SemEval 2024 Task 9: A Comparative Study of Advanced Language Models for Commonsense Reasoning SEMEVAL 2024
IASBS at SemEval-2024 Task 10: Delving into Emotion Discovery and Reasoning in Code-Mixed Conversations SEMEVAL 2024
MorphingMinds at SemEval-2024 Task 10: Emotion Recognition in Conversation in Hindi-English Code-Mixed Conversations SEMEVAL 2024
Muharaf: Manuscripts of Handwritten Arabic Dataset for Cursive Text Recognition NIPS 2024
Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD NIPS 2024
PetKaz at SemEval-2024 Task 8: Can Linguistics Capture the Specifics of LLM-generated Text? SEMEVAL 2024
Credit Attribution and Stable Compression NIPS 2024
Why Do We Need Weight Decay in Modern Deep Learning? NIPS 2024
Anomaly Heterogeneity Learning for Open-set Supervised Anomaly Detection CVPR 2024
DUTh at SemEval 2024 Task 8: Comparing classic Machine Learning Algorithms and LLM based methods for Multigenerator, Multidomain and Multilingual Machine-Generated Text Detection SEMEVAL 2024
The Effects of Data Quality on Named Entity Recognition EACL 2024
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate NIPS 2024
DaVinci at SemEval-2024 Task 9: Few-shot prompting GPT-3.5 for Unconventional Reasoning SEMEVAL 2024
DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving NIPS 2024
$\epsilon$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise NIPS 2024