“2021-08-30”版本间的差异

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(7位用户的9个中间修订版本未显示)
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!People !! This Week !! Next Week !! Task Tracking (<font color="red">DeadLine</font>)
 
!People !! This Week !! Next Week !! Task Tracking (<font color="red">DeadLine</font>)
 
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|Dong Wang
 
|Dong Wang
 
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* Neural PCA experiments on FashionMNIST and kMNIST, [http://192.168.0.51:5555/cgi-bin/cvss/cvss_request.pl?account=wangd&step=view_request&cvssid=830 link]
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* Some variants of NPCA, in terms of sampling scheme, loss function, etc.
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* Some work for thermal paper review
 
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* TASLP paper response
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* Continue the NPCA and paper review.
 
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|Yunqi Cai
 
|Yunqi Cai
 
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* TASLP paper experiments and response
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* Thermal Speaking project
 
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|Lantian Li
 
|Lantian Li
 
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* Prepare multi-modal datasets of CN-Celeb.
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* Monitor cvss 808 and 831.
 
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* Paper of `Hard trials'
 
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|Haoran Sun
 
|Haoran Sun
 
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* emotion recognition on MSP-IMPROV
 
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* subjective evaluation
 
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|Di Wang
 
|Di Wang
 
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* Complete cross-channel experiment doc.
 
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* Data processing for CNC1 and CNC2.
 
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|Pengqi Li
 
|Pengqi Li
 
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* Compare MAML and R-MAML on MiniImagenet for Fast Adaptation
 
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* study of [808]
 
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|Weida Liang
 
|Weida Liang
 
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* Try a two-step training to improve the baseline exemplar encoder
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* Collect test data of the method
 
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* Continue another possible method on multi-step training.
 
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2021年8月30日 (一) 06:07的最后版本

People This Week Next Week Task Tracking (DeadLine)
Dong Wang
  • Neural PCA experiments on FashionMNIST and kMNIST, link
  • Some variants of NPCA, in terms of sampling scheme, loss function, etc.
  • Some work for thermal paper review
  • TASLP paper response
  • Continue the NPCA and paper review.
Yunqi Cai
  • TASLP paper experiments and response
  • Thermal Speaking project
Lantian Li
  • Prepare multi-modal datasets of CN-Celeb.
  • Monitor cvss 808 and 831.
  • Paper of `Hard trials'
Ying Shi
Haoran Sun
  • emotion recognition on MSP-IMPROV
  • subjective evaluation
Jiao Han
Di Wang
  • Complete cross-channel experiment doc.
  • Data processing for CNC1 and CNC2.
Tiankai Zhi
Chen Chen
  • read paper about SN-net(two branchs DAE)
  • attend graduate freshman lectures
  • run UASR code
  • attend graduate freshman lectures
Jingxin Shen
Pengqi Li
  • Compare MAML and R-MAML on MiniImagenet for Fast Adaptation
  • study of [808]
Qingyang Zhu
Weida Liang
  • Try a two-step training to improve the baseline exemplar encoder
  • Collect test data of the method
  • Continue another possible method on multi-step training.