搜索结果: 1-15 共查到“计算机科学技术 M-learning”相关记录208条 . 查询时间(0.109 秒)
苏州大学计算机科学与技术学院杨壮老师的论文在机器学习顶级期刊Journal of Machine Learning Research （JMLR）上在线发表（图）
杨壮 机器学习 Journal of Machine Learning Research
2024/2/3
苏州大学计算机科学与技术学院杨壮副教授撰写的论文“Improved Powered Stochastic Optimization Algorithms for Large-Scale Machine Learning”在机器学习顶级期刊Journal of Machine Learning Research（JMLR）上在线发表，杨壮副教授为该论文的唯一作者，苏州大学计算机科学与技术学院为该论文...
Researchers from MIT, the MIT-IBM Watson AI Lab, IBM Research, and elsewhere have developed a new technique for analyzing unlabeled audio and visual data that could improve the performance of machine-...
Why is machine learning trending in medical research but not in our doctor’s offices?（图）
Bioengineering Penn Integrates Knowledge Professors Computer Science
2023/6/27
Machine learning (ML) programs computers to learn the way we do—through the continual assessment of data and identification of patterns based on past outcomes. ML can quickly pick out trends in big da...
Maybe you can’t tell a book from its cover, but according to researchers at MIT you may now be able to do the equivalent for materials of all sorts, from an airplane part to a medical implant. Their n...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Towards Provably Efficient Quantum Algorithms for Nonlinear Dynamics and Large-scale Machine Learning Models
非线性动力学 机器学习模型 高效量子算法
2023/4/13
Nonlinear dynamics play a prominent role in many domains and are notoriously difficult to solve. Whereas previous quantum algorithms for general nonlinear equations have been severely limited due to t...
It’s no secret that OpenAI’s ChatGPT has some incredible capabilities — for instance, the chatbot can write poetry that resembles Shakespearean sonnets or debug code for a computer program. These abil...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Forecasting Inflation with Economic Narratives and Machine Learning
经济叙事 机器学习 通货膨胀
2023/4/23
In this paper we apply economic narratives to inflation forecasting using a large news corpus and machine learning algorithms. We measure economic narratives quantitatively from the full text content ...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Structure-preserving machine learning moment closures for the radiative transfer equation
辐射传递方程 结构保持 机器学习 矩闭包
2023/4/24
In this talk, we present our work on structure-preserving machine learning (ML) moment closure models for the radiative transfer equation. Most of the existing ML closure models are not able to guaran...
Study shows how machine learning could predict rare disastrous events, like earthquakes or pandemics（图）
机器学习 自然灾害 顺序采样技术
2023/6/26
Researchers from Brown and MIT suggest how scientists can circumvent the need for massive data sets to forecast extreme events with the combination of an advanced machine learning system and sequentia...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Markov decision process and reinforcement learning for intelligent
智能 马尔可夫 决策过程 强化学习
2023/4/28
本次讲座主要针对智能运维中的建模优化问题。首先基于前期研究，我将讨论基于马尔可夫决策过程的有限周期的视情维护策略。考虑二元件系统以及系统元件的退化过程具有随机相关性，用二元伽马过程来描述系统退化过程。系统元件服从周期性检测，当元件的退化程度超过预防性维护阈值时，其会被替换。该维护问题可以表示成马尔可夫决策过程并可用动态规划来求解。不同于无限周期的维护策略，有限周期的最优策略是动态的，其在每次检测都...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Markov decision process and reinforcement learning for intelligent operation and maintenance
智能 马尔可夫 决策过程 强化学习
2023/4/28
本次讲座主要针对智能运维中的建模优化问题。首先基于前期研究，我将讨论基于马尔可夫决策过程的有限周期的视情维护策略。考虑二元件系统以及系统元件的退化过程具有随机相关性，用二元伽马过程来描述系统退化过程。系统元件服从周期性检测，当元件的退化程度超过预防性维护阈值时，其会被替换。该维护问题可以表示成马尔可夫决策过程并可用动态规划来求解。不同于无限周期的维护策略，有限周期的最优策略是动态的，其在每次检测都...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Condensation in deep learning
深度学习 凝结 神经网络
2023/4/28
Why do neural networks (NN) that look so complex usually generalize well? To understand this problem, we find some simple implicit regularizations during training NNs. The first is the frequency princ...
Busy GPUs: Sampling and pipelining method speeds up deep learning on large graphs（图）
GPU 流水线 大型图形 深度学习
2023/6/20
Graphs, a potentially extensive web of nodes connected by edges, can be used to express and interrogate relationships between data, like social connections, financial transactions, traffic, energy gri...
Picture two teams squaring off on a football field. The players can cooperate to achieve an objective, and compete against other players with conflicting interests. That’s how the game works.
A Cornell-led collaboration used machine learning to pinpoint the most accurate means, and timelines, for anticipating the advancement of Alzheimer’s disease in people who are either cognitively norma...