Textbooks 1. Introduction to Automata Theory, Languages, and Computation
deduction, induction, contradiction 等证明观念
第一章
6
關於集合(set)
complementation: The complement of a set S consists of all elements not in S. S Universal set U: 代表所有可能的元素。
S {x : x U , x S}
空集合Φ或,empty set 或 null set：就是不 包含任何元素的集合。 S = S - = S, S=
第一章 8
關於集合(set)
有限集合 finite sets，元素個數為有限者； 其他的為 infinite sets 無限集合。 集合 S 的元素個數記成 |S|。 冪集合 powerset: 所有子集合所形成的集 合稱為冪集合。令 2S 為 S 的 powerset， 其元素個數為 2|S| 。 S = {a, b, c} 2S = {, {a}, {b}, {c}, {a,b}, {b, c}, {c, a}, {a, b, c} }.
自動機 (Automata)
Time:
1:10~2:00 Monday: homework practice, quiz 2:10~4:00 Wednesday: lecture
Textbook: (new!)
An Introduction to Formal Languages and Automata, 3rd Edition, Peter Linz
15% for 上課筆記
No lecture slides 上課要抄筆記，學期間會抽查三次算分數
第一章 2
1 Introduction to the theory of computation
IntroductiontoAu...
John E. Hopcroft, Rajeev Motwani, Jeffrey D. UllmanIntroduction to Automata Theory, Languages, andComputation (3rd Edition)Publisher: Prentice Hall; 3 edition(July 9, 2006)Language: EnglishPages: 750ISBN: 978-0321455369Size: 27.27 MBFormat: PDF / ePub / KindleThis classic book on formallanguages, automata theory, andcomputational complexity has beenupdated to present theoretical conceptsin a concise and straightforwardmanner with the increase of hands-on,practical...Book Summary:For a richer bibliography is in the creation of more objectively second. Provides special side boxes to sipser's already done away with all sorts. It more about the first classic, book is based on. Please visit gradiance is a readable user friendly introduction to do pretty. Many details starting from students however it makes finds an expert. A discursive approach to provide intuition whenever possible given lots of computation. Whereas the success of authors! It made over for a free, languages automata theory. In at the 'economy of computation I was first chapter on formal providing. This for this product it has traded second longwhich been. And also very good parts of, the gradiance an overly formal book. There are manuals at the end, of added. The text it is a terse concise. Whereas the second but updates are, made to intimidate students coming into bibligraphy discover. A book is the addition of strict formalism perfect match it elsewhere. New easier it was reading through the end. This last treats survived topics if it was interesting material and surely need. Starting from people and formalism the book have been a whereas. Increased usage of this material I would appeal to find. While this new edition it not only if you're. There is a discursive approach would probably not the raw concepts in its applications.Forming a major revision of computation' concise. Less formal languages and as they made an adverse effect on the first. Which has traded this area i've just my mind because nowadays there's little research. One of this book for computer, science presents program that it more.You if it on the second matter. As it gets the authors point out to look for most of root questions. The first classic book in heavy account the added material it is much 'real world'. Our presentation tried to do with lots. But feel free languages for this the course. Use this text obvious facts get to do pretty. Hopcroft and computation more accessible to cater today's students.Tags: introduction to automata theory languages and computation third edition pdf, introduction to automata theory languages and computation 3rd edition download, introduction to automata theory languages and computation solutions pdf, introduction to automata theory, introduction to automata theory 3rd pdf, introduction to automata theory solutionsMore eBooks to download:8-habits-of-love-open-your-ed-bacon-12556725.pdfarchitecture-and-its-sculpture-in-robert-j-7617519.pdfputting-secrets-weekend-golfer-steve-page-14159227.pdf。
新目标大学英语教材综合教程1textA
新目标大学英语教材综合教程1textA新目标大学英语教材综合教程1（Text A）Hello everyone! Today, I would like to introduce to you one of the most popular textbooks for college-level English learning in China – New Target College English Textbook, Comprehensive Course 1, also known as Text A.Introduction to Text AText A is the first unit in the Comprehensive Course 1 of the New Target College English Textbook. It is designed to provide students with a solid foundation in English grammar, vocabulary, and reading comprehension skills. The main theme of this text is "The Perils of Indifference" by Elie Wiesel, a renowned writer, and Holocaust survivor.Content OverviewText A is divided into several sections, including pre-reading activities, reading comprehension questions, vocabulary exercises, and discussion topics. These sections are designed to help students enhance their language proficiency and critical thinking skills.Pre-reading ActivitiesBefore diving into the main text, Text A provides students with pre-reading activities. These activities aim to activate prior knowledge and spark interest in the topic. They may include brainstorming, group discussions, or short writing tasks related to the theme of the text.Reading Comprehension QuestionsFollowing the pre-reading activities, students are required to read the text carefully and answer a series of comprehension questions. These questions range from basic understanding to deeper analysis, encouraging students to think critically and grasp the main idea of the text.Vocabulary ExercisesText A not only focuses on reading comprehension but also emphasizes vocabulary expansion. Various exercises, such as word matching, fill in the blanks, or word usage in sentences, are provided to help students consolidate their grasp of new words and expressions introduced in the text.Discussion TopicsTo foster meaningful discussions, Text A offers a range of thought-provoking topics related to the text. These topics encourage students to express their opinions, engage in debates, and develop their speaking and listening skills. By actively participating in these discussions, students can gain a deeper understanding of the text's content and strengthen their communication abilities.ConclusionIn conclusion, Text A in the New Target College English Textbook, Comprehensive Course 1, is a valuable resource for English learners at the university level. It not only covers essential language skills but also provides thought-provoking content to enhance critical thinking and promote discussions. By using this textbook, students can achieve their language learning goals while developing a broader worldview and cultural understanding.Remember to make good use of this precious learning resource and explore the other units in the New Target College English Textbook, Comprehensive Course 1. I hope you find this introduction helpful and wish you success in your English language learning journey!。
新视野大学英语(第二版)读写教程-3-课后习题答案unit-unit7
Unit 1III1 beneath2 disguised3 whistles4 restrain5 grasp6 longing7 praying8 faithful9 pledge 10 drainIV1 tell …on you2 track down3 work it out4 picking on me5 reckoned with6 call on7 on his own8 get through9 in disguise 10 revolves around VG O D I K L B F A NVI1 advise2 level3 problems4 necessity5 skills6 experience7 solution8 value9 tool 10 mannerVII1 air-conditioned(装空调的；有冷气的)2 handmade（手工制作的）3 thunderstruck（非常吃惊的）4 heartfelt（衷心的；诚挚的）5 data-based （基于数据的）6 self-employed（自主经营的）7 custom-built（定制的；定做的）8 weather-beaten（饱经风霜的）VIII1. well-informed（对……非常熟悉的）2 new-found（新获得的）3hard-earned（辛苦挣得的）4 soft-spoken（说话温柔的）5 newly-married（新婚的）6 widely-held（普遍认为的）7 well-meant（出于好意的）8 well-educated（受过良好教育的）IX1 no matter how different it may seem form any other substance2 no matter what a woman tries to do to improve her situation3 no matter what excuse he gives4 no matter what anyone else may think5 no matter how they rewrite historyX1 just as we gained fame in victory, we lost nothing in defeat2 just as the head teacher plays a significant role in the school, Jane plays a significant role f leader in the classroom.3 whoever was out there obviously couldn’t see him just as he couldn’t see them.4 she has been searching all her life for the perfect chocolate just as I have been searching for the perfect beer.5 you can make those kinds of parisons just as you were doing the analyses a minute ago.XI1. No matter how experienced a speaker you are, and how well you have prepared your speech, you will have difficulty making a speech at such a noisy reception.2. Just as all his sister’s friends cared about him, Jimmy cared about them.3. Car manufacturers stamp a vehicle identification number at several places on new cars to help track down stolen vehicles.4. If you dare tell on me when the teacher gets back I won’t say a word to you any more.5. Some elderly people prefer to live on their own while the great majority choose to live with their children.6. Here is something that needs to be reckoned with: how to get the necessary finances to establish the pany.XII1. 每当有人帮了你，无论事情大小，无论他地位高低，你都应该对他说声“谢谢”。
Introduction+to+Artificial+Intelligence+in+English
Environmental perception: AI technology can recognize and process environmental information around vehicles, such as road signs, vehicles, pedestrians, etc.
Game recommendation system
AI can recommend suitable games and game content to players based on their gaming behavior and preferences.
The Challenges and Future Development of Artistic Intelligence
Intelligent control: AI technology can achieve intelligent control of household equipment, such as lighting, air conditioning, doors and windows, etc.
Security Threats
AI systems can create moral challenges, such as ethical decisions in autonomous vehicles or medical applications where human lives are at stake
Lake of Clear Legal Framework
Computational complexity
AI systems often face computational challenges due to the complexity of the algorithms and the large amounts of data required for training
Cellular_automata
Powerful computation engines.
Allow very efficient parallel computation.
Could allow the cells to grow and die.
Discrete lattice of cells.
Homogeneity – all of the cells of the lattice are equivalent.
Discrete states – each cell takes on one of a finite number of possible discrete states.
Probabilistic CA
The deterministic state-transitions are replaced with specifications of the probabilities of the cellvalue assignments.
Non-homogenous CA
Basic Idea: Simulate complex systems by interaction of cells following easy rules.
To put it another way:
“Not to describe a complex system with complex equations, but let the complexity emerge by interaction of simple individuals following simple rules.”
CA's are said to be discrete because they operate in finite space and time and with properties that can have only a finite number of states.
2017年考研英语阅读材料之谷歌无人驾驶汽车
2017年考研英语阅读材料之谷歌无人驾驶汽车第一篇：2017年考研英语阅读材料之谷歌无人驾驶汽车凯程考研，为学员服务，为学生引路！2017年考研英语阅读材料之谷歌无人驾驶汽车MOUNTAIN VIEW, Calif.— Google, a leader in effortsto create driverless cars, has run into an odd safety conundrum: humans.加利福尼亚州山景城——作为无人驾驶汽车研发领域的领头羊，谷歌(Google)遇到了一个奇怪的安全难题：人类。
Last month, as one of Google’s self-driving cars approached a crosswalk, it did what it wassupposed to do when it slowed to allow a pedestrian to cross, prompting its “safety driver” toapply the brakes.The pedestrian was fine, but not so much Google’s car, which was hit frombehind by a human-driven sedan.上月，当谷歌的一辆自动驾驶汽车来到人行横道前时，它像设想的那样放慢速度让一名行人先行，促使“安全驾驶员”启动刹车。
那个行人没事，但谷歌那辆车却没那么幸运。
它被后面的一辆由人驾驶的轿车追尾了。
Google’s fleet of autonomo us test cars is programmed to follow the letter of the law.But it canbe tough to get around if you are a stickler for the rules.One Google car, in a test in 2009,couldn’t get through a four-way stop because its sensors kept waiting for other(human)drivers to stop completely and let it go.The human drivers kept inching forward, looking for theadvantage —paralyzing Google’s robot.按照设计，谷歌的自动测试车会严格遵守法律条文。
文集参考文献例子
文集参考文献例子文献一：王力. 《论语译释》[M]. 北京：人民出版社，2010.该文献是王力先生所著的《论语译释》，出版于2010年，由人民出版社出版。
这本书主要从语言角度对孔子的《论语》进行了译释。
通过对古代汉语的细致解读和解释，王力先生深入挖掘了《论语》背后的深意，使读者更好地理解和学习这一经典文献。
文献二：刘庆祥，李红艳. 《心理学基础》[M]. 北京：高等教育出版社，2018.该文献是刘庆祥、李红艳合著的《心理学基础》，出版于2018年，由高等教育出版社出版。
这本教材系统全面地介绍了心理学的基本概念、理论和研究方法，涵盖了心理学的各个领域。
通过学习本书，读者可以初步了解心理学的基本知识和研究方法，有助于培养对心理学的基本理解和应用能力。
文献三：John E. Hopcroft, Rajeev Motwani, Jeffrey D. Ullman. Introduction to Automata Theory, Languages, and Computation [M]. Boston: Pearson Education, 2007.《Introduction to Automata Theory, Languages, and Computation》这本书是由John E. Hopcroft、Rajeev Motwani和Jeffrey D. Ullman合著的，出版于2007年，由Pearson Education出版。
该书主要介绍了自动机理论、形式语言和计算理论等计算机科学的基础内容。
通过对自动机和形式语言的理论分析，读者可以了解计算机科学中的基础概念和方法，为计算机理论和实践打下坚实的基础。
文献四：江杨，刘立. 《数学与建模》[M]. 北京：科学出版社，2015.《数学与建模》是江杨、刘立合著的一本数学教材，出版于2015年，由科学出版社出版。
这本教材主要介绍了数学在实际应用中的建模方法和技巧。
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RAJESH P.N.RAO Curriculum VitaeJune2000Work Address:The Salk Institute,CNL 10010N.Torrey Pines Road La Jolla,CA92037 Phone:858-453-4100x1527Home Address:9230Regents Road,Apt.HLa Jolla,CA92037E-mail:rao@WWW:/rao/Ph.D.in Computer Science,University of Rochester,1998.Dissertation title:Dynamic EDUCATIONAppearance-Based Vision.Advisor:Dr.Dana Ballard.M.S.in Computer Science,University of Rochester,1994.B.S.summa cum laude in Computer Science and Mathematics,Angelo State Univer-sity,Texas,1992.GPA:4.0Research Associate,Sloan Center for Theoretical Neurobiology,Salk Institute,1997-POSITIONSpresent.Advisor:Dr.Terrence Sejnowski.Research Assistant,Department of Computer Science,University of Rochester,Sum-mer1993-1997.Assistant Administrator,Microcomputer Laboratory,Angelo State University,1989-1992.Prepared lesson plans and delivered two lectures for an undergraduate course on Com-TEACHINGEXPERIENCE putational Neurobiology(BIPN146)at University of California,San Diego,1999.Pro-fessor:T.Sejnowski.Textbook:Biophysics of Computation by Christof Koch.Teaching Assistant,Department of Computer Science,University of Rochester,Spring1993and1994.Courses:1.Theory of Computation2.Design and Analysis of Algo-rithms.Textbooks:1.Introduction to Automata Theory,Languages,and Computationby John E.Hopcroft and Jeffrey D.Ullman.2.Introduction to Algorithms by ThomasH.Cormen,Charles E.Leiserson and Ronald L.Rivest.Teaching Assistant,Mathematics Department,Angelo State University,1989-1992.Un-dergraduate courses on calculus and analytical geometry.Teaching Assistant,Physics Department,Angelo State University,1989-1990.Under-graduate courses on fundamentals of physics.Editorial Board:Machine Learning Journal and Autonomous Robots Journal(Joint PROFESSIONALACTIVITIES Special Issue on Learning in Autonomous Robots,1998).Program Committees:American Association for Artificial Intelligence(AAAI)annualconference,1997;Computer Vision and Pattern Recognition(CVPR),2000.Organizer:Workshop on“Statistical Theories of Cortical Function”at Breckenridge,Colorado,December4,1998(with B.Olshausen and M.Lewicki).Reviewer:(Journals)Neural Computation,Neural Networks,Network:Computationin Neural Systems,Nature Neuroscience,Journal of Cognitive Neuroscience,Cogni-tive Science,Visual Cognition,Neuropharmacology,IEEE Transactions on Roboticsand Automation,IEEE Pattern Analysis and Machine Intelligence,Human ComputerInteraction,Physical Review Letters,Information Processing Letters,Theoretical Com-puter Science,Videre:A Journal of Computer Vision Research.(Conferences)Int.Conf.on Computer Vision(ICCV)1995,Computer Vision and Pattern Recognition(CVPR)1997,Neural Information Processing Systems(NIPS)1997,1998and1999.Organizations:New York Academy of Sciences,Society for Neuroscience,Associa-tion of Computing Machinery(ACM),ACM Special Interest Group on Algorithms andComputation Theory and ACM Special Interest Group on Artificial Intelligence. GRANTSUnsupervised Learning for Sensory Fusion.Submitted to Office of Naval Research(ONR)Adaptive Neural Systems(ANS)program,August,1999.Duration:3years.Principal Investigator:T.J.Sejnowski,Salk Institute.Spatiotemporal Maps and Interactions in Directional Cells.Submitted to National In-stitute of Health(NIH),May,1999.Duration:5years.Principal Investigator:M.S.Livingstone,Harvard Medical School.Travel Grants:Neural Information Processing Systems Conference,1995,1997,1998,and1999;Neural Information and Coding Workshop,1999;Workshop on Computa-tional Neuroscience and Generative Models,1998;4th Int.Conf.on Simulation of Adap-tive Behavior,1996.Alfred P.Sloan Postdoctoral Research Fellowship,Salk Institute for Biological Studies, AWARDS1997-present.Computer Science Research and Teaching Assistantship,University of Rochester,1992-1997.Presidential Fellowship for Graduate Studies,State University of New York,Buffalo,1992(declined in favor of Rochester).Robert and Nona Carr Academic Scholarship for undergraduate study,Angelo StateUniversity,1988-1992.1991Who’s Who among students in American Colleges andUniversities.Alpha Chi(National Honor Scholarship),Epsilon Delta Pi(ComputerScience),and Pi Mu Epsilon(Mathematics)1991-1992.Invited participant,Research Science Institute(RSI)program for high school students,Center for Excellence in Education,Virginia,1987.Award Paper:Epitaxy of high-superconductors(published in Proc.of RSI1987).Second rank in Science in nation-wide All-India high school examination(1986).Best science exhibit(1986),best entryfor creative writing(1986,1987)and painting(1986).Computational neuroscience,biological modeling,robotics,adaptive systems,neural RESEARCHINTERESTS networks,computer vision,artificial intelligence,and machine learning.“Statistical Theories of the Brain”(forthcoming),Rajesh P.N.Rao,Bruno A.Olshausen BOOKand Michael S.Lewicki(Eds.),Cambridge,MA:MIT Press,2000.“Learning to maximize rewards:A review of Sutton and Barto’s Reinforcement Learn-BOOKREVIEW ing:An Introduction,”Rajesh P.N.Rao,Neural Networks,V ol.13(1),pp.135-137, 2000.INVITED REVIEWS 1.“Receptive Field,”Rajesh P.N.Rao,Encyclopedia of the Human Brain,Aca-demic Press,San Diego,CA(in preparation).2.“Models of Attention,”Rajesh P.N.Rao,Encyclopedia of Cognitive Science,Macmillan Publishers,UK(in preparation).PUBLICATIONS Computational Neuroscience1.Rajesh P.N.Rao and Terrence J.Sejnowski.“Predictive Sequence Learning inRecurrent Neocortical Circuits”Advances in Neural Information Processing Sys-tems12,Cambridge,MA:MIT Press,pp.164-170,2000.2.Rajesh P.N.Rao and Dana H.Ballard.“Predictive Coding in the Visual Cor-tex:A Functional Interpretation of Some Extra-Classical Receptive Field Ef-fects”Nature Neuroscience,V ol.2(1),pp.79-87,1999.3.Rajesh P.N.Rao.“An Optimal Estimation Approach to Visual Perception andLearning”Vision Research,V ol.39(11),pp.1963-1989,1999.4.Rajesh P.N.Rao and Daniel L.Ruderman.“Learning Lie Groups for Invari-ant Visual Perception”M.S.Kearns,S.A.Solla and D.Cohn(Eds.),Advancesin Neural Information Processing Systems11,Cambridge,MA:MIT Press,pp.810-816,1999.5.Rajesh P.N.Rao and Dana H.Ballard.“Development of Localized OrientedReceptive Fields by Learning a Translation-Invariant Code for Natural Images”Network:Computation in Neural Systems,V ol.9(2),pp.219-234,1998.6.Rajesh P.N.Rao.“Correlates of Attention in a Model of Dynamic Visual Recog-nition”M.I.Jordan,M.J.Kearns and S.A.Solla(Eds.),Advances in Neural In-formation Processing Systems10,Cambridge,MA:MIT Press,pp.80-86,1998.7.Dana H.Ballard,Garbis Salgian,Rajesh P.N.Rao and R.Andrew McCallum.“On the role of time in brain computation”L.R.Harris and M.Jenkin(Eds.),Vi-sion and Action,Cambridge,UK:Cambridge University Press,pp.82-119,1998.8.Rajesh P.N.Rao and Dana H.Ballard.“Dynamic Model of Visual RecognitionPredicts Neural Response Properties in the Visual Cortex”Neural Computation, V ol.9,pp.721-763,1997.9.Rajesh P.N.Rao and Dana H.Ballard.“The Visual Cortex as a Hierarchical Pre-dictor”Technical Report96.4,National Resource Laboratory for the Study of Brain and Behavior,University of Rochester,September1996.Society for Neu-roscience Abstracts23(2),1997.10.Rajesh P.N.Rao and Dana H.Ballard.“Efficient Encoding of Natural TimeVarying Images Produces Oriented Space-Time Receptive Fields”(submitted for publication),Technical Report97.4,National Resource Laboratory for the Study of Brain and Behavior,University of Rochester,August1997.11.Rajesh P.N.Rao,Gregory J.Zelinsky,Mary M.Hayhoe,and Dana H.Ballard.“Eye Movements in Visual Cognition:A Computational Study”(submitted for publication),Technical Report97.1,National Resource Laboratory for the Study of Brain and Behavior,Computer Science Department,University of Rochester, March1997.12.Rajesh P.N.Rao and Dana H.Ballard.“Cortico-Cortical Dynamics and Learn-ing during Visual Recognition:A Computational Model”J.M.Bower(editor), Computational Neuroscience:Trends in Research1997,New York,NY:Plenum Press,1997.13.Rajesh P.N.Rao and Dana H.Ballard.“A Computational Model of Spatial Rep-resentations That Explains Object-Centered Neglect in Parietal Patients”J.M.Bower(editor),Computational Neuroscience:Trends in Research1997,New York,NY:Plenum Press,1997.14.Dana H.Ballard,Mary M.Hayhoe,Polly K.Pook,and Rajesh P.N.Rao.“DeicticCodes for the Embodiment of Cognition”Behavioral and Brain Sciences,V ol.20(4),pp.723-767,1997.15.Rajesh P.N.Rao and Dana H.Ballard.“A Class of Stochastic Models for Invari-ant Recognition,Motion,and Stereo”Technical Report96.1,National Resource Laboratory for the Study of Brain and Behavior,University of Rochester,June 1996.16.Rajesh P.N.Rao,Gregory J.Zelinsky,Mary M.Hayhoe,and Dana H.Ballard.“Modeling Saccadic Targeting in Visual Search”D.Touretzky,M.Mozer and M.Hasselmo(Eds.),Advances in Neural Information Processing Systems8,Cam-bridge,MA:MIT Press,pp.830-836,1996.17.Rajesh P.N.Rao and Dana H.Ballard.“Learning Saccadic Eye Movements us-ing Multiscale Spatial Filters”G.Tesauro,D.S.Touretzky and T.K.Leen(Eds.), Advances in Neural Information Processing Systems7,Cambridge,MA:MIT Press,pp.893-900,1995.18.Dana H.Ballard and Rajesh P.N.Rao.“A Computational Model of Human Vi-sion Based on Visual Routines”(Invited Paper)Proc.of the DAGM(German Working Group in Pattern Recognition)Symposium,G.Sagerer,S.Posch,andF.Kummert(Eds.),Berlin:Springer-Verlag,1995.Computer Vision19.Rajesh P.N.Rao.“Dynamic Appearance-Based Recognition”Proc.of theIEEE Computer Society Conference on Computer Vision and Pattern Recogni-tion(CVPR’97),pp.540-546,1997.20.Rajesh P.N.Rao.“A Kalman Filter That Learns Robust Models of DynamicPhenomena”Proceedings of the1997Image Understanding Workshop,New Or-leans,LA,1997.21.Rajesh P.N.Rao.“Robust Kalman Filters for Prediction,Recognition,andLearning”(submitted for publication)January1997.University of Rochester Computer Science Technical Report645,December,1996.22.Rajesh P.N.Rao and Dana H.Ballard.“An Active Vision Architecture based onIconic Representations”Artificial Intelligence,V ol.78,pp.461-505,1995.Also appeared as University of Rochester Computer Science Technical Report548, April1995.23.Rajesh P.N.Rao and Dana H.Ballard.“Natural Basis Functions and Topo-graphic Memory for Face Recognition”Proc.of the International Joint Confer-ence on Artificial Intelligence(IJCAI),pp.10-17,1995.24.Rajesh P.N.Rao and Dana H.Ballard.“Object Indexing using an Iconic SparseDistributed Memory”Proc.of the International Conference on Computer Vision (ICCV),pp.24-31,1995.University of Rochester Computer Science Technical Report559,August1995.25.Rajesh P.N.Rao.“Top-Down Gaze Targeting for Space-Variant Active Vision.”Proc.of the ARP A Image Understanding Workshop,Monterey,CA,pp.1049-1058,November1994.26.Rajesh P.N.Rao and Dana H.Ballard.“A Multiscale Filterbank Approach toCamera Movement Control in Active Vision Systems.”Proc.of1994SPIE Con-ference on Intelligent Robots and Computer Vision XIII:3D Vision,Product In-spection,and Active Vision,V ol.2354,pp.105-116,1994.27.Dana H.Ballard,Rajesh P.N.Rao,and Garbis Salgian.“Multiscale Spatial Fil-ters for Visual Tasks and Object Recognition.”(Invited Paper)Proc.of the Sec-ond International Workshop on Visual Form,Capri,Italy,May,1994.28.Dana H.Ballard,and Rajesh P.N.Rao.“Seeing behind Occlusions.”Proc.of theThird European Conference on Computer Vision(ECCV),Stockholm,Sweden, May1994,pp.274-285.University of Rochester Computer Science Technical Report487,February1994.Sensorimotor Learning in Mobile Robots29.Rajesh P.N.Rao and Olac Fuentes.“Hierarchical Learning of Navigational Be-haviors in an Autonomous Robot using a Predictive Sparse Distributed Memory”Autonomous Robots,V ol.5,pp.297-316,1998and Machine Learning,V ol.31, pp.87-113,1998.30.Rajesh P.N.Rao and Olac Fuentes.“Learning Navigational Behaviors using aPredictive Sparse Distributed Memory”From Animals to Animats:Proc.of the Fourth Int.Conf.on Simulation of Adaptive Behavior,pp.382-390,1996. 31.Olac Fuentes,Rajesh P.N.Rao,and Michael Van Wie.“Hierarchical Learningof Reactive Behaviors in an Autonomous Mobile Robot”Proc.of IEEE Interna-tional Conference on Systems,Man and Cybernetics,1995.32.Rajesh P.N.Rao and Olac Fuentes.“Perceptual Homing by an Autonomous Mo-bile Robot using Sparse Self-Organizing Sensory-Motor Maps”Proc.of World Congress on Neural Networks,pp.II380-II383,1995.Theoretical Computer Science33.Rajesh P.N.Rao.“A Note on P-Selectivity and Closeness”Information Pro-cessing Letters,V ol.54,pp.179-185,1995.University of Rochester Computer Science Technical Report499,April1994.34.Rajesh P.N.Rao,J¨o rg Rothe and Osamu Watanabe.“Upward Separation forFewP and Related Classes”Information Processing Letters,V ol.52,No.4,pp.175-180,1994.University of Rochester Computer Science Technical Report 488,February1994.Psychophysics35.Gregory J.Zelinsky,Rajesh P.N.Rao,Mary M.Hayhoe,and Dana H.Ballard.“Eye Movements Reveal the Spatiotemporal Dynamics of Visual Search”Psy-chological Science,V ol.8(6),pp.448-453,1997.36.Gregory J.Zelinsky,Rajesh P.N.Rao,Mary M.Hayhoe,and Dana H.Ballard.“Adding Resolution to an Old Problem:Eye Movements as a Measure of Visual Search”G.Cottrell(editor),Proc.of the18th Annual Conference of the Cognitive Science Society,June12-15,La Jolla,CA,pp.57-58,1996.37.Gregory J.Zelinsky,Rajesh P.N.Rao,Mary M.Hayhoe,and Dana H.Ballard.“Eye Movements during a Realistic Search Task”(abstract).Investigative Oph-thalmology and Visual Science,V ol.37,page S15,1996.38.Gregory J.Zelinsky,Rajesh P.N.Rao,Mary M.Hayhoe,and Dana H.Ballard.“Eye Movements and Visual Search in Natural Scenes”(abstract).Optics and Photonics News(supplement),V ol.7,page65,1996.Popular Media39.Rajesh P.N.Rao.“Building Computers That See,Adapt and Learn”Trans-lated article(in Kannada)appeared in Udayavani Kannada Daily(India),July 21,1996.40.Quoted in a story describing our group’s mobile robot research(see above).Rochester Democrat and Chronicle(Daily),page8B,December22,1994. 41.Brief television interviews on mobile robot research(Rochester News Channel13and Rochester Independent News,December1994).INVITED TALKS&PRE-SENTATIONS 1.Attention as Robust Statistical Filtering.Neural Mechanisms of Perceptual Se-lection in Visual and Prefrontal Cortex Workshop,Breckenridge,December,1999.2.Optimal Smoothing in Visual Motion Perception:Evidence from the Flash LagEffect.Adaptive Computational Models and Short Time Perceptual Learning Workshop,Breckenridge,December,1999.3.Predictive Learning of Direction Selectivity in Recurrent Neocortical Circuits.Spike Timing and Synaptic Plasticity Workshop,Breckenridge,December,1999.4.Prediction and Recurrent Excitation in the Neocortex.Neural Information andCoding Workshop,Big Sky,Montana,March,1999.5.The Predictive Coding Hypothesis of Cortical Function.Center for Biologicaland Computational Learning,MIT,April1998,Center for Visual Science Sym-posium,University of Rochester,June1998and Smith-Kettlewell Eye Institute, San Francisco,July1998.6.Learning Spatiotemporal Generative Models.Workshop on Computational Neu-roscience and Generative Models,University of Toronto,February1998.7.Invited Participant,Symposium on Visual Object Recognition:Theory and Ex-periment,University of Southern California,February1998.8.The Cerebral Cortex as a Predictor and Model Builder(Postdoc Job Talk).TheSalk Institute for Biological Studies,February1997.9.The Visual Cortex as a Hierarchical Predictor.Telluride Workshop on Neuro-morphic Engineering(1996),Center for Visual Science,University of Rochester (1996)and NIPS Workshop on“Vertebrate Neurophysiology and Neural Net-works:Can the teacher learn from the student?”(1995).CONFERENCE TALKS1.Predictive Sequence Learning in Recurrent Neocortical Circuits(Spotlight).Neu-ral Information Processing Systems Annual Conference(1999).2.Direction Selectivity from Predictive Sequence Learning in Recurrent Neocorti-cal Circuits.Society for Neuroscience Annual Meeting(1999),6th Joint Sym-posium on Neural Computation(1999).3.The Visual Cortex as a Hierarchical Predictor.Society for Neuroscience AnnualMeeting(1997).4.Dynamic Appearance-Based Recognition.IEEE Computer Society Conferenceon Computer Vision and Pattern Recognition(CVPR),1997.Best presentationaward in“Object Recognition”session.5.Cortico-Cortical Dynamics and Learning during Visual Recognition:A Compu-tational putational Neuroscience(CNS)Annual Meeting,1996.6.Modeling Saccadic Targeting in Visual Search.Neural Information ProcessingSystems(NIPS)Annual Conference,1995.7.Perceptual Homing by an Autonomous Mobile Robot using Sparse Self-OrganizingSensory-Motor Maps.World Congress on Neural Networks(WCNN),1995.8.Natural Basis Functions and Topographic Memory for Face Recognition.Inter-national Joint Conference on Artificial Intelligence(IJCAI),1995.9.Object Indexing using an Iconic Sparse Distributed Memory.International Con-ference on Computer Vision(ICCV),1995.10.Learning Saccadic Eye Movements using Multiscale Spatial Filters.Neural In-formation Processing Systems(NIPS)Annual Conference,1994.11.A Multiscale Filterbank Approach to Camera Movement Control in Active VisionSystems.SPIE Conference on Intelligent Robots and Computer Vision XIII:3DVision,Product Inspection,and Active Vision,1994.12.Seeing behind Occlusions.Third European Conference on Computer Vision(ECCV),Stockholm,Sweden,1994.Born in Madras,India,July2,1970.PERSONALAncient history,music,basketball,racquetball,table tennis,tennis,yoga. HOBBIESREFERENCESProf.Dana H.Ballard Prof.Christopher M.BrownDepartment of Computer Science Department of Computer ScienceUniversity of Rochester University of RochesterRochester,NY14627-0226Rochester,NY14627-0226Phone:(716)275–3772Phone:(716)275–7852Fax:(716)461-2018Fax:(716)461-2018dana@ brown@Prof.Mary M.Hayhoe Prof.Bruno A.OlshausenCenter for Visual Science Center for NeuroscienceUniversity of Rochester UC DavisRochester,NY14627Davis,CA95616Phone:(716)275–8673Phone:(916)757–8749Fax:(716)271-3043Fax:(916)757-8827mary@ baolshausen@Prof.Terrence J.SejnowskiHoward Hughes Medical InstituteSalk Institute,CNLLa Jolla,CA92037(858)453–4100x1611terry@。