-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathindex.html
More file actions
576 lines (471 loc) · 30.1 KB
/
index.html
File metadata and controls
576 lines (471 loc) · 30.1 KB
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
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
<!DOCTYPE html>
<html>
<head>
<link rel="stylesheet" href="bootstrap/css/bootstrap.min.css">
<script src="./js/jquery-3.3.1.min.js"></script>
<link rel="stylesheet" href="mystyle.css">
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0,shrink-to-fit=no">
<meta name="description" content="This is Jacky Yibo Zhang's homepage">
<meta name="keywords" content="yibo jacky zhang, jacky Y. zhang, yiboz, zyb233, uiuc, ustc, 张益博">
<meta name="robots" content="all">
<meta name="author" content="Jacky Y. Zhang">
<title>Yibo Jacky Zhang</title>
</head>
<body class="body_bg">
<header class="container" id="my_header">
<div class="row">
<span class="col-md-3 col-0" id="main_header_tab"></span>
<span class="col-md-2 col-4" id="main_header_tab">
HOME
</span>
<span class="col-md-2 col-4"id="main_header_tab">
<a href="my_cv.pdf" title="Yibo Zhang CV" class="header_link">CV</a>
</span>
<span class="col-md-2 col-4"id="main_header_tab">
<!--<a href="https://www.youtube.com/watch?v=K17df81RL9Y" title="click" class="header_link_1" >CLICK</a> -->
<a href="https://yiboz407f.myportfolio.com" title="bait" class="header_link">CLICKBAIT</a>
</span>
<span class="col-md-3 col-0" id="main_header_tab"></span>
</div>
<div id="header_background"></div>
</header>
<section class="container" id="box">
<div class="row" id="content_bg">
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="short_bio">
<div id="Hi" style="padding-bottom:0;">
Hi, I'm Yibo (Jacky) Zhang
</div>
<div id="Hi" style="padding-top: 0;">
<!-- 你好，我是张益博 -->
</div>
<div id="profile_photo">
<image src="profile_photo_circle.png" title="profile_photo" width="240px" height="240px"></image>
<br><br>
<span id="caption">photo taken in Vancouver, Canada</span>
</div>
I am a PhD student in the Department of Computer Science at Stanford University, where I am fortunate to be advised by
<a href="https://cs.stanford.edu/~sanmi/index.html" title="Sanmi Koyejo" class="paper_href"> Sanmi Koyejo</a>.
I am also a member of the <a href="https://neuroscience.stanford.edu/initiatives-centers/center-mind-brain-computation-and-technology" title="Center for Mind, Brain, Computation and Technology" class="paper_href">(MBCT)</a> program under Wu Tsai Neurosciences Institute.
<br><br>
<p>
I'm interested in solving <b>fundamental AI problems through theoretical research</b> that leads to <b>real-world solutions</b>. <br><br>
Currently, my research focuses on <b>learning in systems composed of dynamically and stochastically interacting components</b>, particularly how such systems can give rise to <b>autonomous machine intelligence</b>. Pease see my selected works for more details.
</p>
<!--
<ul style="list-style-type:circle; margin-left: 1em;">
<li>
<strong>Intelligent Fields:</strong>
A framework for objective‑driven dynamical stochastic fields, where decentralized entities interact with local neighbors and co-evolve within a dynamic environment to achieve specific objectives.
</li>
<li>
<strong>Machine Learning:</strong>
Model alignment, federated learning, adversarial robustness, active learning.
</li>
<li>
<strong>Optimization:</strong>
Bayesian coresets and combinatorial (particularly submodualr) optimization.
</li>
<li>
<strong>Algorithms:</strong>
Approximation algorithms and practical heuristics.
</li>
</ul>
-->
<!-- <i>Due to uncovered reasons, Yibo Zhang (张益博) used an academic pseudonyms: Jacky Y. Zhang. </i> -->
</span>
<span class="col-md-2 col-1"></span>
</div>
</section>
<!-- Education & Intern -->
<section class="container" id="box" >
<div class="row" id="content_bg">
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="bardivide"> </span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="heading">
Education
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="maincontent">
<b>Stanford University</b><image src="./stanford_logo.png" title="stanford" width=90px style="float:right"></image>
<ul style="list-style-type:circle">
<li>PhD Student - Department of Computer Science (present)</li>
</ul>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="maincontent">
<b>University of Illinois at Urbana-Champaign</b><image src="./uiuc_logo.png" title="uiuc" width=90px style="float:right"></image>
<ul style="list-style-type:circle">
<li>M.S. in Computer Science (2022)</li>
</ul>
</span>
<span class="col-md-2 col-1"></span>
<!-- <span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="maincontent">
<b>Tencent </b> <image src="./tencent_logo.png" title="tencent" width=90px style="float:right"></image>
<ul style="list-style-type:circle">
<li>Research Intern at WeChat Group</li>
<li>Summer 2019</li>
</ul>
</span>
<span class="col-md-2 col-1"></span> -->
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="maincontent">
<b>University of Science and Technology of China </b> <image src="./ustc_logo.gif" title="ustc" width=90px style="float:right"></image>
<ul style="list-style-type:circle">
<li>B.E. in Computer Science (2019)</li>
</ul>
</span>
<span class="col-md-2 col-1"></span>
</div>
</section>
<!-- Publications -->
<section class="container" id="box">
<div class="row" id="content_bg">
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="bardivide"> </span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="heading">
Publications & Preprints
<br>
<font size="+0">(*eqaul contribution)</font>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="firstsmallheading">
<b>Selected</b>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Exploring Dynamical Stochastic Field Theory for General Autonomous Learning </b>
<br>
Yibo Jacky Zhang, Sanmi Koyejo. <br>
Work in progress. <br>
<ul>
<li>
<i>An important open problem in the science of artificial intelligence is how to build autonomous agents that learns continuously in unknown environments using local observations. </i>
</li>
<li>
<i>This paper explores this problem through dynamical stochastic neural networks, where each neuron acts as a simple agent that continuously adapts through local learning rules. The learning requires no resets, replay buffers, context windows, or backpropagation.</i>
</li>
</ul>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>A Framework for Objective-Driven Dynamical Stochastic Fields </b>
[ <a href="https://arxiv.org/abs/2504.16115v2" title="A Framework for Objective-Driven Dynamical Stochastic Fields" class="paper_href">pdf</a> ]
<br>
Yibo Jacky Zhang, Sanmi Koyejo. <br>
Preprint, 2025. <br>
<ul>
<li>
<i>It is challenging to describe complex systems composed of interacting and dynamic components. In particular, it becomes more challenging as these components in the system exhibit objective-driven behaviors. </i>
</li>
<li>
<i>This paper develops a formal and elegant description of such systems using a field-theoretic language inspired by physics. The proposed theoretical framework is referred to as intelligent fields. </i>
</li>
</ul>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Aligning Compound AI Systems via System-level DPO </b>
[ <a href="https://arxiv.org/abs/2502.17721" title="Aligning Compound AI Systems via System-level DPO" class="paper_href">pdf</a> ]
<!-- [ <a href="./files/aaai2025-sysDPO.pdf" title="poster" class="paper_href">poster</a> ] -->
<br>
Xiangwen Wang*, Yibo Jacky Zhang*, Zhoujie Ding, Katherine Tsai, Sanmi Koyejo. <br>
Neural Information Processing
Systems (NeurIPS), 2025.
<ul>
<li>
<i>Compound AI systems, comprising multiple interacting components such as LLMs and diffusion models, have demonstrated improvements compared to single models. However, aligning compound AI systems to human preferences is challenging. </i>
</li>
<li>
<i>We propose a principled framework (SysDPO) for aligning all components in a compound AI system as a cohesive whole. </i>
</li>
</ul>
</span>
<span class="col-md-2 col-1"></span>
<!-- <span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting </b>
[ <a href="https://openreview.net/forum?id=6J3ehSUrMU" title="Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting" class="paper_href">pdf</a> ]
<br>
Enyi Jiang*, Yibo Jacky Zhang*, Oluwasanmi Koyejo. <br>
International Conference on Learning Representations (ICLR), 2024.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization </b>
[ <a href="https://arxiv.org/abs/2202.01832" title="Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization" class="paper_href">pdf</a> ]
[ <a href="./files/icml22-poster.pdf" title="poster" class="paper_href">poster</a> ]
[ <a href="https://slideslive.com/38983737/adversarially-robust-models-may-not-transfer-better-domain-transferability-from-the-view-of-regularization?ref=search-presentations-Adversarially+Robust+Models+may+not+Transfer+Better" title="short talk" class="paper_href">talk</a> ]
<br>
Xiaojun Xu*, Jacky Y. Zhang*, Evelyn Ma, Danny Son, Oluwasanmi Koyejo, Bo Li. <br>
International Conference on Machine Learning (ICML), 2022.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective</b>
<br>
[ <a href="https://arxiv.org/abs/2007.00715" title="Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective" class="paper_href">pdf</a> ]
[ <a href="./files/bayesian_coreset_optimization_aistais_poster.pdf" title="poster" class="paper_href">poster</a> ]
[ <a href="https://slideslive.at/38953354/bayesian-coresets-revisiting-the-nonconvex-optimization-perspective?ref=search" title="short talk" class="paper_href">short talk</a> ]
[ <a href="https://slideslive.at/38953402/oral-bayesian-coresets-revisiting-the-nonconvex-optimization-perspective?ref=speaker-17421-latest" title="long_talk" class="paper_href">long talk</a> ]
<br>
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo. <br>
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021. (Oral)
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability </b>
[ <a href="https://arxiv.org/abs/2006.14512" title="Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability" class="paper_href">pdf</a> ]
[ <a href="./files/poster-transferability-ICML21.pdf" title="poster" class="paper_href">poster</a> ]
[ <a href="https://slideslive.com/38958855/uncovering-the-connections-between-adversarial-transferability-and-knowledge-transferability?ref=search" title="short talk" class="paper_href">talk</a> ]
<br>
Kaizhao Liang*, Jacky Y. Zhang*, Boxin Wang, Zhuolin Yang, Oluwasanmi Koyejo, Bo Li <br>
International Conference on Machine Learning (ICML), 2021.
</span>
<span class="col-md-2 col-1"></span> -->
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="firstsmallheading">
<b>List of All</b>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Latent Adversarial Regularization for Offline Preference Optimization </b>
[ <a href="https://arxiv.org/abs/2601.22083" title="Latent Adversarial Regularization for Offline Preference Optimization" class="paper_href">pdf</a> ]
<br>
Enyi Jiang, Yibo Jacky Zhang, Yinglun Xu, Andreas Haupt, Nancy Amato, Sanmi Koyejo. <br>
Preprint, 2026. <br>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Improving Single-round Active Adaptation: A Prediction Variability Perspective </b>
[ <a href="https://openreview.net/pdf?id=Vthqn5VE7L" title="Improving Single-round Active Adaptation: A Prediction Variability Perspective" class="paper_href">pdf</a> ]
<br>
Xiaoyang Wang, Yibo Jacky Zhang, Olawale Elijah Salaudeen, Mingyuan Wu, Hongpeng Guo, Chaoyang He, Klara Nahrstedt, Sanmi Koyejo. <br>
Transactions on Machine Learning Research (TMLR), 2025. <br>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>A Framework for Objective-Driven Dynamical Stochastic Fields </b>
[ <a href="https://arxiv.org/abs/2504.16115v2" title="A Framework for Objective-Driven Dynamical Stochastic Fields" class="paper_href">pdf</a> ]
<br>
Yibo Jacky Zhang, Sanmi Koyejo. <br>
Preprint, 2025.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Aligning Compound AI Systems via System-level DPO </b>
[ <a href="https://arxiv.org/abs/2502.17721" title="Aligning Compound AI Systems via System-level DPO" class="paper_href">pdf</a> ]
<!--[ <a href="./files/aaai2025-sysDPO.pdf" title="poster" class="paper_href">poster</a> ] -->
<br>
Xiangwen Wang*, Yibo Jacky Zhang*, Zhoujie Ding, Katherine Tsai, Sanmi Koyejo. <br>
Neural Information Processing
Systems (NeurIPS), 2025.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Probing Human Visual Robustness with Neurally-Guided Deep Neural Networks </b>
[ <a href="https://arxiv.org/pdf/2405.02564" title="Probing Human Visual Robustness with Neurally-Guided Deep Neural Networks" class="paper_href">pdf</a> ]
<br>
Zhenan Shao, Linjian Ma, Yiqing Zhou, Yibo Jacky Zhang, Sanmi Koyejo, Bo Li, Diane M Beck. <br>
Preprint, 2024.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Can Public Large Language Models Help Private Cross-device Federated Learning? </b>
[ <a href="https://arxiv.org/abs/2305.12132" title="Can Public Large Language Models Help Private Cross-device Federated Learning?" class="paper_href">pdf</a> ]
<br>
Boxin Wang, Yibo Jacky Zhang, Yuan Cao, Bo Li, H. Brendan McMahan, Sewoong Oh, Zheng Xu, Manzil Zaheer. <br>
NAACL 2024.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting </b>
[ <a href="https://openreview.net/forum?id=6J3ehSUrMU" title="Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting" class="paper_href">pdf</a> ]
<br>
Enyi Jiang*, Yibo Jacky Zhang*, Oluwasanmi Koyejo. <br>
International Conference on Learning Representations (ICLR), 2024.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Batch Active Learning from the Perspective of Sparse Approximation </b>
[ <a href="https://arxiv.org/abs/2211.00246" title="Batch Active Learning from the Perspective of Sparse Approximation" class="paper_href">pdf</a> ]
[ <a href="./files/neurips22-AL-sparse.pdf" title="poster" class="paper_href">poster</a> ]
<br>
Maohao Shen*, Bowen Jiang*, Jacky Y. Zhang*, Oluwasanmi Koyejo. <br>
NeurIPS 2022 Workshop on Human in the Loop Learning.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization </b>
[ <a href="https://arxiv.org/abs/2202.01832" title="Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization" class="paper_href">pdf</a> ]
[ <a href="./files/icml22-poster.pdf" title="poster" class="paper_href">poster</a> ]
[ <a href="https://slideslive.com/38983737/adversarially-robust-models-may-not-transfer-better-domain-transferability-from-the-view-of-regularization?ref=search-presentations-Adversarially+Robust+Models+may+not+Transfer+Better" title="short talk" class="paper_href">talk</a> ]
<br>
Xiaojun Xu*, Jacky Y. Zhang*, Evelyn Ma, Danny Son, Oluwasanmi Koyejo, Bo Li <br>
International Conference on Machine Learning (ICML), 2022.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective</b>
<br>
[ <a href="https://arxiv.org/abs/2007.00715" title="Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective" class="paper_href">pdf</a> ]
[ <a href="./files/bayesian_coreset_optimization_aistais_poster.pdf" title="poster" class="paper_href">poster</a> ]
[ <a href="https://slideslive.at/38953354/bayesian-coresets-revisiting-the-nonconvex-optimization-perspective?ref=search" title="short talk" class="paper_href">short talk</a> ]
[ <a href="https://slideslive.at/38953402/oral-bayesian-coresets-revisiting-the-nonconvex-optimization-perspective?ref=speaker-17421-latest" title="long_talk" class="paper_href">long talk</a> ]
<br>
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo. <br>
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021. (Oral)
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability </b>
[ <a href="https://arxiv.org/abs/2006.14512" title="Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability" class="paper_href">pdf</a> ]
[ <a href="./files/poster-transferability-ICML21.pdf" title="poster" class="paper_href">poster</a> ]
[ <a href="https://slideslive.com/38958855/uncovering-the-connections-between-adversarial-transferability-and-knowledge-transferability?ref=search" title="short talk" class="paper_href">talk</a> ]
<br>
Kaizhao Liang*, Jacky Y. Zhang*, Boxin Wang, Zhuolin Yang, Oluwasanmi Koyejo, Bo Li <br>
International Conference on Machine Learning (ICML), 2021.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Labeling Cost-Sensitive Batch Active Learning for Brain Tumor Segmentation</b>
<!-- [ <a href="https://arxiv.org/abs/2007.00715" title="Bayesian Coresets: An Optimization Perspective" class="paper_href">pdf</a> ]<br> -->
<br>
Maohao Shen, Jacky Y. Zhang, Leihao Chen, Weiman Yan, Neel Jani, Brad Sutton, Oluwasanmi Koyejo. <br>
International Symposium on Biomedical Imaging (ISBI), 2021.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Robusta: Robust AutoML for Feature Selection via Reinforcement Learning</b>
[ <a href="https://arxiv.org/pdf/2101.05950.pdf" title="Robusta: Robust AutoML for Feature Selection via Reinforcement Learning" class="paper_href">pdf</a> ]<br>
Xiaoyang Wang, Bo Li, Yibo Zhang, Bhavya Kailkhura, Klara Nahrstedt. <br>
AAAI 2021 Workshop Towards Robust, Secure and Efficient Machine Learning.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Learning Sparse Distributions using Iterative Hard Thresholding </b>
[ <a href="https://arxiv.org/abs/1910.13389" title="Learning Sparse Distributions using Iterative Hard Thresholding" class="paper_href">pdf</a> ]
[ <a href="./files/distIHT_poster.pdf" title="poster" class="paper_href">poster</a> ]
<br>
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo. <br>
Neural Information Processing
Systems (NeurIPS), 2019.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>Maximizing Monotone DR-submodular Continuous Functions by Derivative-free Optimization</b>
[ <a href="https://arxiv.org/abs/1810.06833" title="Continuous Functions Derivative-free" class="paper_href">pdf</a> ] <br>
Yibo Zhang, Chao Qian, Ke Tang. <br>
Preprint: arXiv 1810.06833, 2018.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="paperlist">
<b>On Multiset Selection with Size Constraints</b>
[ <a href="https://pdfs.semanticscholar.org/4b4e/2d0699918230e0905a2249ce12dc244514b9.pdf" title="On Multiset Selection with Size Constraints" class="paper_href">pdf</a> ]<br>
Chao Qian, Yibo Zhang, Ke Tang, Xin Yao. <br>
AAAI Conference on Artificial Intelligence (AAAI), 2018.
</span>
<span class="col-md-2 col-1"></span>
</div>
</section>
<!-- Contact -->
<section class="container" id="box">
<div class="row" id="content_bg">
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="bardivide"> </span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="heading">
Contact
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="maincontent">
<span id="contact">
yiboz@stanford.edu <br>
</span>
</span>
<span class="col-md-2 col-1"></span>
</div>
</section>
<!-- Others -->
<section class="container" id="box">
<div class="row" id="content_bg">
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="bardivide"> </span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="heading">
Miscellaneous
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="maincontent">
<span id="contact">
I like to ponder random things. For example: Would aliens also have their mouths near their brains? Will artificial and biological intelligence eventually converge?
How much could I contribute to scientific progress if I were sent back in time 1000 years? And, most importantly, why are you still reading all this nonsense? <br>
</span>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="maincontent">
<b>Photographer of Today:</b> <a href="https://www.mattstuart.com/all-that-life-can-afford" title="Photographer" class="paper_href">Matt Stuart</a> <image src="./photo.jpeg" title="photo" width=200px style="float:right"></image>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="maincontent">
<b>Music of Today:</b> <a href="https://www.youtube.com/watch?v=pTmTlwZcli0" title="song" class="paper_href">A Love Song</a> - EGO WRAPPIN' <image src="./song_cover.jpeg" title="song" width=150px style="float:right"></image>
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="maincontent">
I will probably update these tomorrow almost surely with high probability.
</span>
<span class="col-md-2 col-1"></span>
<span class="col-md-2 col-1"></span>
<span class="col-md-8 col-10" id="bardivide"> </span>
<span class="col-md-2 col-1"></span>
</div>
</section>
<!-- Footer -->
<footer id="myfooter">
<div id="back_to_top" style="padding-bottom:0;">
<a href="#my_header" class="header_link"><b>Back to Top</b></a>
<div id="copyright"><a href="https://github.com/jackyzyb/jackyzyb.github.io" class="header_link">
<b>Designed by Yibo Jacky Zhang</b></a>
</div>
</div>
</footer>
</body>
</html>