智能科学课程考核的相关

下周末智能科学考核,主要还是做PPT。这次考核难度比较大,70到80分钟。

于是先查比较重要的会议论文,刚查到A类会议之上还有A+这个级别的。CCF把A类会议挪到一区SCI级别了,曾经投过的ICDE在这个版本里也成了A+。http://blog.csdn.net/cserchen/article/details/40508181

AAAI National Conference of the American Association for Artificial Intelligence A+
AAMAS International Conference on Autonomous Agents and Multiagent Systems A+
ACL Association of Computational Linguistics A+
ACMMM ACM Multimedia Conference A+
ASPLOS Architectural Support for Programming Languages and Operating Systems A+
CAV Computer Aided Verification A+
CCS ACM Conference on Computer and Communications Security A+
CHI International Conference on Human Factors in Computing Systems A+
COLT Annual Conference on Computational Learning Theory A+
CRYPTO Advances in Cryptology A+
CSCL Computer Supported Collaborative Learning A+
DCC IEEE Data Compression Conference A+
DSN International Conference on Dependable Systems A+
EuroCrypt International Conference on the Theory and Application of Cryptographic Techniques A+
FOCS IEEE Symposium on Foundations of Computer Science A+
FOGA Foundations of Genetic Algorithms A+
HPCA IEEE Symposium on High Performance Computer Architecture A+
I3DG ACM-SIGRAPH Interactive 3D Graphics A+
ICAPS International Conference on Automated Planning and Scheduling A+
ICCV IEEE International Conference on Computer Vision A+
ICDE IEEE International Conference on Data Engineering A+
ICDM IEEE International Conference on Data Mining A+
ICFP International Conference on Functional Programming A+
ICIS International Conference on Information Systems A+
ICML International Conference on Machine Learning A+
ICSE International Conference on Software Engineering A+
IJCAI International Joint Conference on Artificial Intelligence A+
IJCAR International Joint Conference on Automated Reasoning A+
INFOCOM Joint Conference of the IEEE Computer and Communications Societies A+
InfoVis IEEE Information Visualization Conference A+
IPSN Information Processing in Sensor Networks A+
ISCA ACM International Symposium on Computer Architecture A+
ISMAR IEEE and ACM International Symposium on Mixed and Augmented Reality A+
ISSAC International. Symposium on Symbolic and Algebraic Computation A+
ISWC IEEE International Symposium on Wearable Computing A+
IWQoS IFIP International Workshop on QoS A+
JCDL ACM Conference on Digital Libraries A+
KR International Conference on Principles of KR & Reasoning A+
LICS IEEE Symposium on Logic in Computer Science A+
MOBICOM ACM International Conferencem on Mobile Computing and Networking A+
NIPS Advances in Neural Information Processing Systems A+
OOPSLA ACM Conference on Object Oriented Programming Systems Languages and Applications A+
OSDI Usenix Symposium on Operating Systems Design and Implementation A+
PERCOM IEEE International Conference on Pervasive Computing and Communications A+
PERVASIVE International Conference on Pervasive Computing A+
PLDI ACM-SIGPLAN Conference on Programming Language Design & Implementation A+
PODC ACM Symposium on Principles of Distributed Computing A+
PODS ACM SIGMOD-SIGACT-SIGART Conferenceon Principles of Database Systems A+
POPL ACM-SIGACT Symposium on Principles of Prog Langs A+
RSS Robotics: Systems and Science A+
RTSS Real Time Systems Symp A+
SENSYS ACM Conference on Embedded Networked Sensor Systems A+
SIGCOMM ACM Conference on Applications, Technologies,Architectures, and Protocols for Computer Communication A+
SIGGRAPH ACM SIG International Conference on Computer Graphics and Interactive Techniques A+
SIGIR ACM International Conference on Research and Development in Information Retrieval A+
SIGKDD ACM International Conference on Knowledge Discovery and Data Mining A+
SIGMETRICS ACM SIG on computer and communications metrics and performance A+
SIGMOD ACM Special Interest Group on Management of Data Conference A+
SODA ACM/SIAM Symposium on Discrete Algorithms A+
SOSP ACM SIGOPS Symposium on Operating Systems Principles A+
STOC ACM Symposium on Theory of Computing A+
UAI Conference in Uncertainty in Artifical Intelligence A+
UbiComp Uniquitous Computing A+
VLDB International Conference on Very Large Databases A+
WWW International World Wide Web Conference A+

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刚在知网上找对应论文,居然弹出并发数达到最大。

生物信息与智能科学,很多书还有文献狭义上的意思就是把统计学习方法用到生物信息上。

VC维:对于一个指示函数集,如果其生长函数是线性的,则它的VC维为无穷大;而如果生长函数以参数为h的对数函数为上界,则函数集的VC维是有限的且等于h。

又函数集学习过程一致收敛的充分必要条件,对任意的样本分布,都有lim[G(n)/n]=0,且这时学习过程收敛速度一定是快的。G(n)为指示函数集的生长函数。

这涉及信息论和熵的问题。于是昨天杜老师提到了卡诺循环热力学定律等等。于是也查了一下。

热力学第一定律是能量守恒定律。 热力学第二定律有几种表述方式: 克劳修斯表述为热量可以自发地从温度高的物体传递到温度低的物体,但不可能自发地从温度低的物体传递到温度高的物体;开尔文-普朗克表述为不可能从单一热源吸取热量,并将这热量完全变为功,而不产生其他影响。以及熵增表述:孤立系统的熵永不减小。 热力学第三定律通常表述为绝对零度时,所有纯物质的完美晶体的熵值为零, 或者绝对零度(T=0)不可达到。

之后搜索引擎右面一堆奇谈怪论。看了之后不如不看。。

回到正题。

昨天杜老师的课主题就是提特征比后期统计学习方法更对提高预测精度有更多影响。貌似现在信号处理之类的都大量地用了。

于是PPT的框架基本清楚了,就是把目前的研究工作作为主要内容,外加一堆生物信息基本知识。

原文地址:https://www.cnblogs.com/ubiwind/p/5593346.html