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<table>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2021ecp">1</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Ytopt/SuRF: Machine-Learning-Based Search for Autotuning.
2021 ECP Annual Meeting, April 2021.
[ <a href="pbalapra-presentations_bib.html#Bal2021ecp">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020siam">2</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
In situ compression artifact removal in scientific data using deep
transfer learning and experience replay.
Impacts of Applied Mathematics and Computer Science on DOE
Computational Science, SIAM Conference on Computational Science and
Engineering, March 2021.
[ <a href="pbalapra-presentations_bib.html#Bal2020siam">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2021sci">3</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Scientific domain-informed machine learning.
Sustainable Horizon Institute, March 2021.
[ <a href="pbalapra-presentations_bib.html#Bal2021sci">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020alcfsdl">4</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
DeepHyper: A Hyperparameter Search Package for Deep Neural
Networks.
ALCF Simulation, Data, and Learning Workshop, Argonne, IL, December
2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020alcfsdl">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020b">5</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Enabling ml approaches to hpc systems operations.
Panel, IEEE Cluster Workshop on Monitoring and Analsis for High
Performance Computing Sytems Plus Applications (HPCMASPA), September 2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020b">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020a">6</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Automated machine learning for molecular chemistry.
Artificial Intelligence for Water Workshop, Argonne, IL, September
2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020a">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020h">7</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
DeepHyper and hyperparameter optimization.
ATPESC 2020: Argonne Training Program on Extreme-Scale Computing,
August 2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020h">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020d">8</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Machine-learning-based automatic performance tuning.
Workshop on Program Synthesis for Scientific Computing, August 2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020d">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020g">9</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
DeepHyper: Scalable Automated Machine Learning Package.
Argonne CPS Division seminar series, August 2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020g">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020c">10</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Keynote – the future of hpc systems in the presence of ai.
Panel, Smoky Mountains Computational Sciences and Engineering
Conference (SMC), August 2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020c">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020alcfcp">11</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
DeepHyper: A Hyperparameter Search Package for Deep Neural
Networks.
ALCF Computational Performance Workshop, Argonne, IL, May 2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020alcfcp">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020e">12</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Artificial intelligence and machine learning.
AI for Sustainability Workshop, April 2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020e">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020f">13</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Reinforcement learning and applications.
SciDAC TDS Meeting, March 2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020f">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020mcsahm">14</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Neuromorphic acceleration for uncertainty quantification in deep
neural networks.
MCS All Hands Meeting, Argonne, IL, January 2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020mcsahm">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020i">15</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Artificial intelligence for science.
TRB ExComm A.I. Policy Session, January 2020.
[ <a href="pbalapra-presentations_bib.html#Bal2020i">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2020j">16</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Scalable reinforcement-learning-based neural architecture search for
cancer research.
SC '19: IEEE/ACM International Conference on High Performance
Computing, Networking, Storage and Analysis, November 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2020j">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019alcfsdl">17</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
DeepHyper: A Hyperparameter Search Package for Deep Neural
Networks.
ALCF Simulation, Data, and Learning Workshop, Argonne, IL, October
2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019alcfsdl">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019alcf">18</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
DeepHyper: A Hyperparameter Search Package for Deep Neural
Networks.
ALCF Developer Session, September 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019alcf">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019m">19</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
AI tools.
PSE AI in Science and Engineering Workshop, Argonne, IL, September
2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019m">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019g">20</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Hyperparameter optimization and DeepHyper.
ATPESC 2019: Argonne Training Program on Extreme-Scale Computing, St.
Charles, IL, August 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019g">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019i">21</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Recurrent networks for time series data.
Argonne Artificial Intelligence for Science Workshop, Argonne, IL,
August 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019i">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019h">22</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Deep learning basics.
Artificial Intelligence for Science Workshop, Argonne, IL, August
2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019h">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019f">23</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Deep learning basics.
ATPESC 2019: Argonne Training Program on Extreme-Scale Computing,
St. Charles, IL, August 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019f">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019j">24</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Deep learning basics.
Artificial Intelligence for Science Workshop for Summer Students,
Argonne, IL, July 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019j">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019k">25</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Recurrent networks for time series data.
Artificial Intelligence for Science Workshop for Summer Students,
Argonne, IL, July 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019k">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019l">26</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Scientific domain-informed machine learning.
Argonne Physics Divison Colloquium, Argonne, IL, May 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019l">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019e">27</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Artificial intelligence to accelerate discovery and development.
Argonne Outloud Public Lecture, Argonne, IL, May 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019e">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019d">28</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
DeepHyper: Scalable Asynchronous Hyperparameter Search for Deep
Learning.
Data Enabled Modeling and Discovery in Science and Engineering
Minisymposium, SIAM Conference on Computational Science and Engineering,
February 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019d">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019c">29</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Machine-learning-based-search for automatic performance tuning.
OMASE 2019: Optimization, Modeling, Analysis and Space Exploration
Workshop, Washington DC, February 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019c">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019b">30</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Machine-learning-based performance modeling and tuning for
high-performance computing.
HPCaML 2019: The First International Workshop on the Intersection
of High Performance Computing and Machine Learning, Washington DC, February
2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019b">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019a">31</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Scalable reinforcement-learning-based neural architecture search for
scientific and engineering applications.
LANS Informal Seminar, Argonne, IL, February 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019a">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2019ldrd">32</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Evaluating deep neural network to spiking neural networks
transformation for DOE scientific applications on Intel Loihi.
2019 LDRD Expedition, Argonne, IL, 2019.
[ <a href="pbalapra-presentations_bib.html#Bal2019ldrd">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018q">33</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Scientific domain-informed machine learning.
Advanced Photon Source Colloquium, Argonne, IL, December 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018q">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018p">34</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Scientific domain-informed machine learning.
Indian Institute of Science, Bengaluru, India, December 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018p">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018o">35</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
DeepHyper: Asynchronous Hyperparameter Search for Deep Neural
Networks.
25th IEEE International Conference on High Performance Computing,
Data, and Analytics, Bengaluru, India, December 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018o">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018i">36</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Scientific domain-informed machine learning.
Consortium for Computational Physics and Chemistry Meeting, Argonne,
IL, November 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018i">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018j">37</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Spatial-temporal deep learning and hyperparameter search for traffic
prediction.
Workshop on Large-Scale Computing for Transportation Studies, Maui,
HI, November 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018j">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018k">38</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Benchmarking machine learning methods for performance modeling of
scientific applications.
PMBS 2018: Performance Modeling, Benchmarking and Simulation of
High Performance Computer Systems, November 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018k">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018m">39</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Scientific domain-informed machine learning.
ALCF Simulation, Data, and Learning Workshop, Argonne, IL, October
2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018m">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018n">40</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Reproducibility, portability and interpretability of deep learning.
Workshop on Deep Learning for Multimessenger Astrophysics: Real-time
Discovery at Scale, October 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018n">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018h">41</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Scientific domain-informed machine learning.
Department Seminar Series, Mechanical and Industrial Engineering,
University of Illinois at Chicago, IL, October 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018h">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018l">42</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Data parallel deep learning.
CANDLE-EXALEARN ECP Workshop, Argonne, IL, October 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018l">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018e">43</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Data for machine learning.
Argonne Geospatial Workshop, August 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018e">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018b">44</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Machine learning hardware.
SciDAC Fusion Machine-Learning Workshop 2018, Princeton, NJ, June
2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018b">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018g">45</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Tools for scientific machine learning.
Army Research Lab Workshop, Chicago, IL, May 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018g">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018f">46</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Machine learning overview and applications.
Argonne Environmental Science Division Retreat, May 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018f">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018a">47</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Machine learning in high performance computing.
7th Greater Chicago Area Systems Research Workshop University of
Chicago, Chicago, IL, April 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018a">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018ldrd">48</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Neuromorphic Acceleration for Approximate Bayesian Inference on
Neural Networks via Permanent Dropout.
2018 LDRD Expedition, Argonne, IL, 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018ldrd">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018d">49</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Recurrent neural networks.
Argonne Deep Learning Workshop, January 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018d">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2018c">50</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Deep learning basics.
Argonne Deep Learning Workshop, January 2018.
[ <a href="pbalapra-presentations_bib.html#Bal2018c">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017c">51</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Introduction to unsupervised and supervised learning in python:
Hands-on tutorial.
Argonne Training Program on Extreme-Scale Computing (ATPESC), St.
Charles, IL, August 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017c">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017b">52</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Overview of machine learning methods.
Argonne Training Program on Extreme-Scale Computing (ATPESC), St.
Charles, IL, August 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017b">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017d">53</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Need for data locality in machine/deep learning.
Fourth Workshop on Programming Abstractions for Data Locality
(PADAL'17), Chicago, IL, August 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017d">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017a">54</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Automatic multi-objective modeling with machine learning.
Argonne Training Program on Extreme-Scale Computing (ATPESC), St.
Charles, IL, August 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017a">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017f">55</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Overview of machine learning methods.
Argonne Machine Learning Workshop, Argonne, IL, July 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017f">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017e">56</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Generative adversarial networks.
US ATLAS Workshop, Argonne, IL, July 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017e">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017i">57</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Introduction to unsupervised and supervised learning in python:
Hands-on tutorial.
Argonne Machine Learning Workshop, Argonne, IL, July 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017i">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017h">58</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Automatic multi-objective modeling with machine learning.
Argonne Machine Learning Workshop, Argonne, IL, July 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017h">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017l">59</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Generative adversarial networks.
The 3rd International Workshop on Data Science in High Energy Physics
(DS@HEP 2017), Fermi National Accelerator Laboratory, IL, May 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017l">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017j">60</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Automatic multi-objective modeling with machine learning.
Workshop on Optimization and Machine Learning (ACNTW 17),
Northwestern University, Argonne, May 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017j">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017k">61</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Analytical performance modeling and validation of intel's xeon phi
architecture.
Computing Frontiers 2017, University of Siena, Siena, Italy, May
2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017k">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017m">62</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Artificial intelligence for transportation and mobility.
Tech Hub, SAE World Congress 2017, Detroit, MI, May 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017m">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017p">63</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Introduction to unsupervised and supervised learning in python:
Hands-on tutorial.
Argonne Machine Learning Workshop, Argonne, IL, April 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017p">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017n">64</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Automatic multi-objective modeling with machine learning.
Argonne Machine Learning Workshop, Argonne, IL, April 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017n">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2017o">65</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Overview of machine learning methods.
Argonne Machine Learning Workshop, Argonne, IL, April 2017.
[ <a href="pbalapra-presentations_bib.html#Bal2017o">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2016e">66</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Machine learning for high performance computing.
Midwest Big Data Opportunities and Challenges, Chicago, IL, September
2016.
[ <a href="pbalapra-presentations_bib.html#Bal2016e">bib</a> ]
</td>
</tr>
<tr valign="top">
<td align="right" class="bibtexnumber">
[<a name="Bal2016d">67</a>]
</td>
<td class="bibtexitem" align="justify">
P. Balaprakash.
Improving data transfer throughput with direct search optimization.
The 45th International Conference on Parallel Processing, ICPP 2016,
Philadelphia, PA, August 2016.
[ <a href="pbalapra-presentations_bib.html#Bal2016d">bib</a> ]
</td>
</tr>
<tr valign="top">