-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathreferences.bib
542 lines (489 loc) · 18.4 KB
/
references.bib
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
@inproceedings{Suri:2016,
title={Analyzing the applicability of internet of things to the battlefield environment},
author={Suri, Niranjan and Tortonesi, Mauro and Michaelis, James and Budulas, Peter and Benincasa, Giacomo and Russell, Stephen and Stefanelli, Cesare and Winkler, Robert},
booktitle={Military Communications and Information Systems (ICMCIS), 2016 International Conference on},
pages={1--8},
year={2016},
organization={IEEE}
}
@article{Kott:2016,
title={The internet of battle things},
author={Kott, Alexander and Swami, Ananthram and West, Bruce J},
journal={Computer},
volume={49},
number={12},
pages={70--75},
year={2016},
publisher={IEEE}
}
@inproceedings{Verma:2017,
author = {Dinesh Verma and Graham Bent and Ian Taylor},
title = {Towards A Distributed Federated Brain Architecture using Cognitive {I}o{T} Devices},
booktitle = {The Ninth International Conference on Advanced Cognitive Technologies and Applications},
year = {2017}
}
@article{LeCun:2015,
title = "Deep learning",
author = "Yann Lecun and Yoshua Bengio and Geoffrey Hinton",
year = "2015",
month = "5",
volume = "521",
pages = "436--444",
journal = "Nature",
number = "7553",
}
@book{Goodfellow:2016,
title={Deep Learning},
author={Ian Goodfellow and Yoshua Bengio and Aaron Courville},
publisher={MIT Press},
note={\url{http://www.deeplearningbook.org}},
year={2016}
}
@article{Bengio:2013,
title = "Representation Learning: A Review and New Perspectives",
author = " Yoshua Bengio and Aaron Courville and Pascal Vincent",
journal = "IEEE Transactions on Pattern Analysis and Machine Intelligence",
year = "2013",
volume = "35",
issue = "8",
pages = "1798--1828",
}
@inproceedings{Szegedy:2015,
author = {Szegedy, Christian and Liu, Wei and Jia, Yangqing and Sermanet, Pierre and Reed, Scott and Anguelov, Dragomir and Erhan, Dumitru and Vanhoucke, Vincent and Rabinovich, Andrew},
title = {Going Deeper With Convolutions},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}
@inproceedings{he2016identity,
title={Identity mappings in deep residual networks},
author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
booktitle={European conference on computer vision},
pages={630--645},
year={2016},
organization={Springer}
}
@inproceedings{he2016deep,
title={Deep residual learning for image recognition},
author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
pages={770--778},
year={2016}
}
@inproceedings{krizhevsky2012imagenet,
title={Imagenet classification with deep convolutional neural networks},
author={Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey E},
booktitle={Advances in neural information processing systems},
pages={1097--1105},
year={2012}
}
@article{lecun1998gradient,
title={Gradient-based learning applied to document recognition},
author={LeCun, Yann and Bottou, L{\'e}on and Bengio, Yoshua and Haffner, Patrick and others},
journal={Proceedings of the IEEE},
volume={86},
number={11},
pages={2278--2324},
year={1998},
publisher={Taipei, Taiwan}
}
@inproceedings{panda2016conditional,
title={Conditional deep learning for energy-efficient and enhanced pattern recognition},
author={Panda, Priyadarshini and Sengupta, Abhronil and Roy, Kaushik},
journal={Design, Automation and Test in Europe Conference and Exhibition (DATE)},
pages={475--480},
year={2016},
organization={IEEE}
}
@inproceedings{parsa2017staged,
title={Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis},
author={Parsa, Maryam and Panda, Priyadarshini and Sen, Shreyas and Roy, Kaushik},
booktitle={2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
pages={78--81},
year={2017},
organization={IEEE}
}
@article{panda2017energy,
title={Energy-efficient and improved image recognition with conditional deep learning},
author={Panda, Priyadarshini and Sengupta, Abhronil and Roy, Kaushik},
journal={ACM Journal on Emerging Technologies in Computing Systems (JETC)},
volume={13},
number={3},
pages={33},
year={2017},
publisher={ACM}
}
@inproceedings{venkataramani2015scalable,
title={Scalable-effort classifiers for energy-efficient machine learning},
author={Venkataramani, Swagath and Raghunathan, Anand and Liu, Jie and Shoaib, Mohammed},
booktitle={Proceedings of the 52nd Annual Design Automation Conference},
pages={67},
year={2015},
organization={ACM}
}
%--------------------
% Spiking references
%--------------------
@article{sengupta2019going,
title={Going Deeper in Spiking Neural Networks: VGG and Residual Architectures},
author={Sengupta, Abhronil and Ye, Yuting and Wang, Robert and Liu, Chiao and Roy, Kaushik},
journal={Frontiers in Neuroscience},
volume={13},
pages={95},
year={2019},
publisher={Frontiers}
}
@article{blouw2018benchmarking,
title={Benchmarking Keyword Spotting Efficiency on Neuromorphic Hardware},
author={Blouw, Peter and Choo, Xuan and Hunsberger, Eric and Eliasmith, Chris},
journal={arXiv preprint arXiv:1812.01739},
year={2018}
}
@article{cao2015spiking,
title={Spiking deep convolutional neural networks for energy-efficient object recognition},
author={Cao, Yongqiang and Chen, Yang and Khosla, Deepak},
journal={International Journal of Computer Vision},
volume={113},
number={1},
pages={54--66},
year={2015},
publisher={Springer}
}
@article{hunsberger2015spiking,
title={Spiking deep networks with LIF neurons},
author={Hunsberger, Eric and Eliasmith, Chris},
journal={arXiv preprint arXiv:1510.08829},
year={2015}
}
@inproceedings{diehl2015fast,
title={Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing},
author={Diehl, Peter U and Neil, Daniel and Binas, Jonathan and Cook, Matthew and Liu, Shih-Chii and Pfeiffer, Michael},
booktitle={2015 International Joint Conference on Neural Networks (IJCNN)},
pages={1--8},
year={2015},
organization={IEEE}
}
@article{rueckauer2017conversion,
title={Conversion of continuous-valued deep networks to efficient event-driven networks for image classification},
author={Rueckauer, Bodo and Lungu, Iulia-Alexandra and Hu, Yuhuang and Pfeiffer, Michael and Liu, Shih-Chii},
journal={Frontiers in neuroscience},
volume={11},
pages={682},
year={2017},
publisher={Frontiers}
}
@article{lee2016training,
title={Training deep spiking neural networks using backpropagation},
author={Lee, Jun Haeng and Delbruck, Tobi and Pfeiffer, Michael},
journal={Frontiers in neuroscience},
volume={10},
pages={508},
year={2016},
publisher={Frontiers}
}
@inproceedings{panda2016unsupervised,
title={Unsupervised regenerative learning of hierarchical features in spiking deep networks for object recognition},
author={Panda, Priyadarshini and Roy, Kaushik},
booktitle={2016 International Joint Conference on Neural Networks (IJCNN)},
pages={299--306},
year={2016},
organization={IEEE}
}
@article{wu2018spatio,
title={Spatio-temporal backpropagation for training high-performance spiking neural networks},
author={Wu, Yujie and Deng, Lei and Li, Guoqi and Zhu, Jun and Shi, Luping},
journal={Frontiers in neuroscience},
volume={12},
year={2018},
publisher={Frontiers Media SA}
}
@article{lee2018training,
title={Training deep spiking convolutional neural networks with STDP-based unsupervised pre-training followed by supervised fine-tuning},
author={Lee, Chankyu and Panda, Priyadarshini and Srinivasan, Gopalakrishnan and Roy, Kaushik},
journal={Frontiers in neuroscience},
volume={12},
year={2018},
publisher={Frontiers Media SA}
}
@inproceedings{jin2018hybrid,
title={Hybrid macro/micro level backpropagation for training deep spiking neural networks},
author={Jin, Yingyezhe and Zhang, Wenrui and Li, Peng},
booktitle={Advances in Neural Information Processing Systems},
pages={7005--7015},
year={2018}
}
@inproceedings{shrestha2018slayer,
title={SLAYER: Spike Layer Error Reassignment in Time},
author={Shrestha, Sumit Bam and Orchard, Garrick},
booktitle={Advances in Neural Information Processing Systems},
pages={1419--1428},
year={2018}
}
@article{neftci2019surrogate,
title={Surrogate Gradient Learning in Spiking Neural Networks},
author={Neftci, Emre O and Mostafa, Hesham and Zenke, Friedemann},
journal={arXiv preprint arXiv:1901.09948},
year={2019}
}
@article{diehl2015unsupervised,
title={Unsupervised learning of digit recognition using spike-timing-dependent plasticity},
author={Diehl, Peter U and Cook, Matthew},
journal={Frontiers in computational neuroscience},
volume={9},
pages={99},
year={2015},
publisher={Frontiers}
}
@article{masquelier2007unsupervised,
title={Unsupervised learning of visual features through spike timing dependent plasticity},
author={Masquelier, Timoth{\'e}e and Thorpe, Simon J},
journal={PLoS computational biology},
volume={3},
number={2},
pages={e31},
year={2007},
publisher={Public Library of Science}
}
@article{srinivasan2018stdp,
title={STDP-based Unsupervised Feature Learning using Convolution-over-time in Spiking Neural Networks for Energy-Efficient Neuromorphic Computing},
author={Srinivasan, Gopalakrishnan and Panda, Priyadarshini and Roy, Kaushik},
journal={ACM Journal on Emerging Technologies in Computing Systems (JETC)},
volume={14},
number={4},
pages={44},
year={2018},
publisher={ACM}
}
@inproceedings{tavanaei2018training,
title={Training Spiking ConvNets by STDP and Gradient Descent},
author={Tavanaei, Amirhossein and Kirby, Zachary and Maida, Anthony S},
booktitle={2018 International Joint Conference on Neural Networks (IJCNN)},
pages={1-8},
doi={10.1109/IJCNN.2018.8489104},
ISSN={2161-4407},
month={July},
year={2018},
address={Rio de Janeiro, Brazil}
}
@article{kheradpisheh2018stdp,
title = "STDP-based spiking deep convolutional neural networks for object recognition",
author = "Saeed Reza Kheradpisheh and Mohammad Ganjtabesh and Simon J. Thorpe and Timothée Masquelier",
journal = "Neural Networks",
volume = "99",
pages = "56--67",
year = "2018",
issn = "0893-6080",
doi = "https://doi.org/10.1016/j.neunet.2017.12.005",
url = "http://www.sciencedirect.com/science/article/pii/S0893608017302903"
}
@article{ferre2018unsupervised,
title={Unsupervised Feature Learning With Winner-Takes-All Based STDP},
author={Ferr{\'e}, Paul and Mamalet, Franck and Thorpe, Simon J},
journal={Frontiers in computational neuroscience},
volume={12},
pages={24},
year={2018},
publisher={Frontiers}
}
@article{Lee-Anytime-2018,
title={Anytime Neural Prediction via Slicing Networks Vertically},
author={Hankook Lee and Jinwoo Shin},
journal={CoRR},
year={2018},
volume={abs/1807.02609}
}
@article{Szegedy-regluar-2015,
title={Going deeper with convolutions},
author={Christian Szegedy and Wei Liu and Yangqing Jia and Pierre Sermanet and Scott E. Reed and Dragomir Anguelov and Dumitru Erhan and Vincent Vanhoucke and Andrew Rabinovich},
journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2015},
pages={1-9}
}
@article{SqueezeNet-2016,
author = {Forrest N. Iandola and
Matthew W. Moskewicz and
Khalid Ashraf and
Song Han and
William J. Dally and
Kurt Keutzer},
title = {SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and {\textless}1MB
model size},
journal = {CoRR},
volume = {abs/1602.07360},
year = {2016},
url = {http://arxiv.org/abs/1602.07360},
archivePrefix = {arXiv},
eprint = {1602.07360},
timestamp = {Mon, 13 Aug 2018 16:46:12 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/IandolaMAHDK16},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{Han-DeepCC-2015,
author = {Song Han and
Huizi Mao and
William J. Dally},
title = {Deep Compression: Compressing Deep Neural Network with Pruning, Trained
Quantization and Huffman Coding},
journal = {CoRR},
volume = {abs/1510.00149},
year = {2015},
url = {http://arxiv.org/abs/1510.00149},
archivePrefix = {arXiv},
eprint = {1510.00149},
timestamp = {Mon, 13 Aug 2018 16:48:14 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/HanMD15},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{Mathieu-Fast-2014,
title={Fast Training of Convolutional Networks through FFTs},
author={Micha{\"e}l Mathieu and Mikael Henaff and Yann LeCun},
journal={CoRR},
year={2014},
volume={abs/1312.5851}
}
@article{Lavin-Fast-2016,
title={Fast Algorithms for Convolutional Neural Networks},
author={Andrew Lavin},
journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2016},
pages={4013-4021}
}
@article{BranchyNet-2016,
title={BranchyNet: Fast inference via early exiting from deep neural networks},
author={Surat Teerapittayanon and Bradley McDanel and H. T. Kung},
journal={2016 23rd International Conference on Pattern Recognition (ICPR)},
year={2016},
pages={2464-2469}
}
@article{thiele2018event,
author={Thiele, Johannes C. and Bichler, Olivier and Dupret, Antoine},
title={Event-Based, Timescale Invariant Unsupervised Online Deep Learning With STDP},
journal={Frontiers in Computational Neuroscience},
volume={12},
pages={46},
year={2018},
url={https://www.frontiersin.org/article/10.3389/fncom.2018.00046},
doi={10.3389/fncom.2018.00046},
issn={1662-5188},
publisher={Frontiers}
}
@article{lee2018deep,
author={C. Lee and G. Srinivasan and P. Panda and K. Roy},
journal={IEEE Transactions on Cognitive and Developmental Systems},
title={Deep Spiking Convolutional Neural Network Trained with Unsupervised Spike Timing Dependent Plasticity},
year={2018},
volume={},
number={},
pages={1-1},
doi={10.1109/TCDS.2018.2833071},
issn={2379-8920},
month={}
}
@article{mozafari2018combining,
title={Combining STDP and Reward-Modulated STDP in Deep Convolutional Spiking Neural Networks for Digit Recognition},
author={Mozafari, Milad and Ganjtabesh, Mohammad and Nowzari-Dalini, Abbas and Thorpe, Simon J and Masquelier, Timoth{\'e}e},
journal={arXiv preprint arXiv:1804.00227},
year={2018}
}
@inproceedings{courbariaux2015binaryconnect,
title={Binaryconnect: Training deep neural networks with binary weights during propagations},
author={Courbariaux, Matthieu and Bengio, Yoshua and David, Jean-Pierre},
booktitle={Advances in neural information processing systems},
pages={3123--3131},
year={2015},
address={Montr{\'e}al, Canada}
}
@inproceedings{rastegari2016xnor,
title={Xnor-net: Imagenet classification using binary convolutional neural networks},
author={Rastegari, Mohammad and Ordonez, Vicente and Redmon, Joseph and Farhadi, Ali},
booktitle={European Conference on Computer Vision},
pages={525--542},
year={2016},
organization={Springer},
address={Amsterdam, The Netherlands}
}
@article{hubara2017quantized,
title={Quantized neural networks: Training neural networks with low precision weights and activations},
author={Hubara, Itay and Courbariaux, Matthieu and Soudry, Daniel and El-Yaniv, Ran and Bengio, Yoshua},
journal={The Journal of Machine Learning Research},
volume={18},
number={1},
pages={6869--6898},
year={2017},
publisher={JMLR.org}
}
@article{suri2013bio,
title={Bio-inspired stochastic computing using binary CBRAM synapses},
author={Suri, Manan and Querlioz, Damien and Bichler, Olivier and Palma, Giorgio and Vianello, Elisa and Vuillaume, Dominique and Gamrat, Christian and DeSalvo, Barbara},
journal={IEEE Transactions on Electron Devices},
volume={60},
number={7},
pages={2402--2409},
year={2013},
publisher={IEEE}
}
@article{querlioz2015bioinspired,
title={Bioinspired programming of memory devices for implementing an inference engine},
author={Querlioz, Damien and Bichler, Olivier and Vincent, Adrien Francis and Gamrat, Christian},
journal={Proceedings of the IEEE},
volume={103},
number={8},
pages={1398--1416},
year={2015},
publisher={IEEE}
}
@article{srinivasan2016magnetic,
title={Magnetic tunnel junction based long-term short-term stochastic synapse for a spiking neural network with on-chip STDP learning},
author={Srinivasan, Gopalakrishnan and Sengupta, Abhronil and Roy, Kaushik},
journal={Scientific reports},
volume={6},
pages={29545},
year={2016},
publisher={Nature Publishing Group}
}
@article{srinivasan2019restocnet,
title={ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing},
author={Srinivasan, Gopalakrishnan and Roy, Kaushik},
journal={Frontiers in Neuroscience},
volume={13},
pages={189},
year={2019},
publisher={Frontiers}
}
@InProceedings{jacob2018quantization,
author = {Jacob, Benoit and Kligys, Skirmantas and Chen, Bo and Zhu, Menglong and Tang, Matthew and Howard, Andrew and Adam, Hartwig and Kalenichenko, Dmitry},
title = {Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}
}
@article{endsley1995toward,
title={Toward a theory of situation awareness in dynamic systems},
author={Endsley, Mica R},
journal={Human factors},
volume={37},
number={1},
pages={32--64},
year={1995},
publisher={SAGE Publications Sage CA: Los Angeles, CA}
}
@inproceedings{preece2017cognitive,
title={Cognitive computing for coalition situational understanding},
author={Preece, Alun and Cerutti, Federico and Braines, Dave and Chakraborty, Supriyo and Srivastava, Mani},
booktitle={2017 IEEE SmartWorld},
pages={1--6},
year={2017},
organization={IEEE}
}
@article{deltaInterpretability,
Author = {Amit Dhurandhar and Vijay Iyengar and Ronny Luss and Karthikeyan Shanmugam},
Title = {A Formal Framework to Characterize Interpretability of Procedures},
Year = {2017},
Journal = {arXiv:1707.03886},
}
@article{TIPInterpretability,
author = {Amit Dhurandhar and Vijay Iyengar and Ronny Luss and Karthikeyan Shanmugam},
title = {{TIP}: Typifying the Interpretability of Procedures},
year = {2017},
Journal = {arXiv:1706.02952},
}