Cost-aware job scheduling for cloud instances using deep reinforcement learning
As the services provided by cloud vendors are providing better performance, achieving auto-
scaling, load-balancing, and optimized performance along with low infrastructure …
scaling, load-balancing, and optimized performance along with low infrastructure …
Deep adversarial imitation reinforcement learning for QoS-aware cloud job scheduling
Although cloud computing is one of the promising technologies for online business services,
how to schedule real-time cloud jobs with high quality of service (QoS) is still challenging …
how to schedule real-time cloud jobs with high quality of service (QoS) is still challenging …
Cost-aware real-time job scheduling for hybrid cloud using deep reinforcement learning
L Cheng, A Kalapgar, A Jain, Y Wang, Y Qin… - Neural Computing and …, 2022 - Springer
Hybrid cloud computing enables enterprises to get the best of both private and public cloud
models. One of its primary benefits is to reduce operational costs, and the prerequisite is that …
models. One of its primary benefits is to reduce operational costs, and the prerequisite is that …
Elastic resource management for deep learning applications in a container cluster
The increasing demand for learning from massive datasets is restructuring our economy.
Effective learning, however, involves nontrivial computing resources. Most businesses utilize …
Effective learning, however, involves nontrivial computing resources. Most businesses utilize …
Progress-based container scheduling for short-lived applications in a kubernetes cluster
In the past decade, we have envisioned enormous growth in the data generated by different
sources, ranging from weather sensors and customer purchasing records to Internet of …
sources, ranging from weather sensors and customer purchasing records to Internet of …
Speculative container scheduling for deep learning applications in a kubernetes cluster
In the past decade, we have witnessed a dramatically increasing volume of data collected
from various sources. To maximize utilization, various machine and deep learning models …
from various sources. To maximize utilization, various machine and deep learning models …
Form 10-q itemization
The quarterly financial statement, or Form 10-Q, is one of the most frequently required filings
for US public companies to disclose financial and other important business information. Due …
for US public companies to disclose financial and other important business information. Due …
Differentiate quality of experience scheduling for deep learning inferences with docker containers in the cloud
With the prevalence of big-data-driven applications, such as face recognition on
smartphones and tailored recommendations from Google Ads, we are on the road to a …
smartphones and tailored recommendations from Google Ads, we are on the road to a …
RLPTO: A reinforcement learning-based performance-time optimized task and resource scheduling mechanism for distributed machine learning
With the wide application of deep learning, the amount of data required to train deep
learning models is becoming increasingly larger, resulting in an increased training time and …
learning models is becoming increasingly larger, resulting in an increased training time and …
机器学习模型在心血管疾病中的应用
蒋子悠 - 智能机器人, 2024 - journals.aspub.org
随着当今社会带给人们的高强度工作生活压力, 心血管疾病问题的日益严峻, 发病率逐年增加,
全球对此类疾病的关注与日俱增. 传统的预测方法虽有一定预测能力, 但是特异性较低 …
全球对此类疾病的关注与日俱增. 传统的预测方法虽有一定预测能力, 但是特异性较低 …