“News-20140526”版本间的差异
| 第1行： | 第1行： | ||
| + | = 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. | ||
2014年9月3日 (三) 06:45的版本
目录
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.
