“News-20140526”版本间的差异

来自cslt Wiki
跳转至: 导航搜索
第1行: 第1行:
= IBM scientists Yong Qin、Songfang Huang、Ming Li visit CSLT =
+
IBM scientists Yong Qin、Songfang Huang、Ming Li visit CSLT
  
 
* Time: 2014-05-26
 
* Time: 2014-05-26
 
* Location: ROOM 1-305, BLDG FIT, Tsinghua University  
 
* Location: ROOM 1-305, BLDG FIT, Tsinghua University  
  
==Cognitive Computing==
+
Cognitive Computing
 
+
 
•      Presenter:
 
•      Presenter:
 
 
–      Kelvin Qin/秦勇
 
–      Kelvin Qin/秦勇
 
 
–      Senior Technical Staff Member
 
–      Senior Technical Staff Member
 
 
–      IBM Research – China
 
–      IBM Research – China
 
 
•      Abstract:
 
•      Abstract:
 
 
In the era of Big Data, the biggest challenge for enterprises today is to re-discover the trends, re-discover the clients, re-define the relationship with customers to satisfy their ever growing demands. We strive to improve enterprise's capability and efficiency to make a smart decision from heterogeneous data sources including structured, semi-structured and unstructured data by developing the cognitive computing technology . The ultimate goal is to provide enterprise and human decision supporting tools for complex problems solving. In this talk, I will brief IBM research strategy on cognitive computing and several technologies we are working on to interact with data naturally and understand data deeply.
 
In the era of Big Data, the biggest challenge for enterprises today is to re-discover the trends, re-discover the clients, re-define the relationship with customers to satisfy their ever growing demands. We strive to improve enterprise's capability and efficiency to make a smart decision from heterogeneous data sources including structured, semi-structured and unstructured data by developing the cognitive computing technology . The ultimate goal is to provide enterprise and human decision supporting tools for complex problems solving. In this talk, I will brief IBM research strategy on cognitive computing and several technologies we are working on to interact with data naturally and understand data deeply.
  
==Advanced Language Modeling==
+
Advanced Language Modeling
  
 
•      Presenter:
 
•      Presenter:
 
 
–      Songfang Huang/黄松芳
 
–      Songfang Huang/黄松芳
 
 
–      Research Staff Member
 
–      Research Staff Member
 
 
–      IBM Research – China
 
–      IBM Research – China
 
 
•      Abstract:
 
•      Abstract:
 
 
Traditional N-gram models are widely used in speech and language processing applications, e.g., speech recognition and machine translation. However, N-gram models suffer from some limitations, due to the Markov assumption. In this talk, we will briefly review several advanced language modeling techniques to go beyond short-span limitations and incorporate additional information sources. The models we will cover include, but not limited to, exponential models, Bayesian models, and neural network models.
 
Traditional N-gram models are widely used in speech and language processing applications, e.g., speech recognition and machine translation. However, N-gram models suffer from some limitations, due to the Markov assumption. In this talk, we will briefly review several advanced language modeling techniques to go beyond short-span limitations and incorporate additional information sources. The models we will cover include, but not limited to, exponential models, Bayesian models, and neural network models.
  
==Multi-factor Mobile Biometric Authentication==
+
Multi-factor Mobile Biometric Authentication
 
+
 
•      Presenter:
 
•      Presenter:
 
 
–      Min Li/李敏
 
–      Min Li/李敏
 
 
–      Staff Researcher Member
 
–      Staff Researcher Member
 
 
–      IBM Research - China
 
–      IBM Research - China
 
 
•      Abstract:
 
•      Abstract:
 
 
–      Mobile business transactions are undergoing a surging growth as the raise of mobile Internet and mobile e-Commerce. Security becomes the top concern of mobile customers and enterprises because of potential risks from lost/stolen or unattended mobile devices. This talk will introduce background of mobile money, IBM's mobile biometric authentication solution and some technical progresses.
 
–      Mobile business transactions are undergoing a surging growth as the raise of mobile Internet and mobile e-Commerce. Security becomes the top concern of mobile customers and enterprises because of potential risks from lost/stolen or unattended mobile devices. This talk will introduce background of mobile money, IBM's mobile biometric authentication solution and some technical progresses.

2014年9月3日 (三) 06:46的版本

IBM scientists Yong Qin、Songfang Huang、Ming Li visit CSLT

  • Time: 2014-05-26
  • Location: ROOM 1-305, BLDG FIT, Tsinghua University

Cognitive Computing • Presenter: – Kelvin Qin/秦勇 – Senior Technical Staff Member – IBM Research – China • Abstract: In the era of Big Data, the biggest challenge for enterprises today is to re-discover the trends, re-discover the clients, re-define the relationship with customers to satisfy their ever growing demands. We strive to improve enterprise's capability and efficiency to make a smart decision from heterogeneous data sources including structured, semi-structured and unstructured data by developing the cognitive computing technology . The ultimate goal is to provide enterprise and human decision supporting tools for complex problems solving. In this talk, I will brief IBM research strategy on cognitive computing and several technologies we are working on to interact with data naturally and understand data deeply.

Advanced Language Modeling

• Presenter: – Songfang Huang/黄松芳 – Research Staff Member – IBM Research – China • Abstract: Traditional N-gram models are widely used in speech and language processing applications, e.g., speech recognition and machine translation. However, N-gram models suffer from some limitations, due to the Markov assumption. In this talk, we will briefly review several advanced language modeling techniques to go beyond short-span limitations and incorporate additional information sources. The models we will cover include, but not limited to, exponential models, Bayesian models, and neural network models.

Multi-factor Mobile Biometric Authentication • Presenter: – Min Li/李敏 – Staff Researcher Member – IBM Research - China • Abstract: – Mobile business transactions are undergoing a surging growth as the raise of mobile Internet and mobile e-Commerce. Security becomes the top concern of mobile customers and enterprises because of potential risks from lost/stolen or unattended mobile devices. This talk will introduce background of mobile money, IBM's mobile biometric authentication solution and some technical progresses.