TA5a: Machine Learning and Hardware Aspects |
Session Type: Oral |
Time: Tuesday, October 30, 08:15 - 09:55 |
Location: Scripps |
Session Chair: Tokunbo Ogunfunmi, Santa Clara University |
TA5a-1: EFFICIENT RECONFIGURABLE HARDWARE CORE FOR CONVOLUTIONAL NEURAL NETWORKS |
Haonan Wang; Nanjing University |
Jun Lin; Nanjing University |
Yi Xie; Rutgers University |
Bo Yuan; Rutgers University |
Zhongfeng Wang; Nanjing University |
TA5a-2: AREA-EFFICIENT K-NEAREST NEIGHBOR DESIGN USING STOCHASTIC COMPUTING |
Yi Xie; Rutgers University |
Chunhua Deng; Rutgers University |
Siyu Liao; Rutgers University |
Bo Yuan; Rutgers University |
TA5a-3: ELASTO-NET: AN HDL CONVERSION FRAMEWORK FOR CONVOLUTIONAL NEURAL NETWORKS |
Anaam Ansari; Santa Clara University |
Tokunbo Ogunfunmi; Santa Clara University |
TA5a-4: BAYESIAN BELIEF NETWORK BASED OCCUPANCY ASSESSMENT FRAMEWORK |
Mohsin M Jamali; University of Texas of Permian Basin |
Golrokh Mirzaei; Ohio State University |