Tag: Supervised Learning
All the articles with the tag "Supervised Learning".
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Always Skip Attention
This paper theoretically demonstrates the ill-conditioning of Self-Attention Blocks in Vision Transformers without skip connections, highlights their role as regularizers, and proposes Token Graying (SVD and DCT) to improve input token conditioning, achieving modest performance gains in supervised and self-supervised tasks.
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RL in Name Only? Analyzing the Structural Assumptions in RL post-training for LLMs
本文通过理论和实验分析,揭示了当前RL(如GRPO)在LLM后训练中的MDP结构假设使其退化为过滤迭代监督微调,并指出响应长度增加源于奖励分配偏差,而非推理能力提升。
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Deep Learning for On-Street Parking Violation Prediction
This paper develops a Deep Learning model with a novel data smoothing technique to predict fine-grained on-street parking violation rates in Thessaloniki, Greece, using indirect features like weather and time, achieving improved accuracy (MAE of 0.146) over baseline methods.
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Large Language Models are Miscalibrated In-Context Learners
本文通过对大型语言模型在低资源场景下的校准问题进行深入分析,揭示上下文学习(ICL)未一致改善校准效果,并提出自集成方法显著提升校准性能(平均降低ECE 43%),同时维持或略提升任务性能。
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Nonparametric learning of covariate-based Markov jump processes using RKHS techniques
本文提出了一种基于再生核希尔伯特空间(RKHS)的非参数化方法,通过频率学和贝叶斯框架建模连续时间马尔可夫链(CTMC)中协变量驱动的非线性转移率,显著提升了个体化状态转移预测的准确性。