No abstract available.
Cited By
- Haigh T (2024). Between the Booms: AI in Winter, Communications of the ACM, 67:11, (18-23), Online publication date: 1-Nov-2024.
- Alari A, Campana L, Ciliberto F, Maggese S, Sgaravatti C, Zanella F, Pisani A and Ferrari Dacrema M Exploiting Contextual Normalizations and Article Endorsement for News Recommendation Proceedings of the Recommender Systems Challenge 2024, (17-21)
- Touretzky D, Chen A and Pawar N (2024). Neural Networks in Middle School, ACM Inroads, 15:3, (24-28), Online publication date: 1-Sep-2024.
- Farina M, Zhdanov P, Karimov A and Lavazza A (2024). AI and society: a virtue ethics approach, AI & Society, 39:3, (1127-1140), Online publication date: 1-Jun-2024.
- Cao X and Vempala S Contrastive moments Proceedings of the 37th International Conference on Neural Information Processing Systems, (72540-72582)
- Edelman B, Goel S, Kakade S, Malach E and Zhang C Pareto frontiers in deep feature learning Proceedings of the 37th International Conference on Neural Information Processing Systems, (48021-48034)
- Kamel N, Kharma N and Perreault J (2023). Evolutionary design and analysis of ribozyme-based logic gates, Genetic Programming and Evolvable Machines, 24:2, Online publication date: 1-Dec-2023.
- Datta D and Friedland G Efficient Multimedia Computing: Unleashing the Power of AutoML Proceedings of the 31st ACM International Conference on Multimedia, (9700-9701)
- Cobb M (2023). The Representation of Knowledge and the Relevance of Biological Models at the Symposium on the Mechanization of Thought Processes, 1958, IEEE Annals of the History of Computing, 45:3, (32-47), Online publication date: 1-Jul-2023.
- Haigh T (2023). Conjoined Twins: Artificial Intelligence and the Invention of Computer Science, Communications of the ACM, 66:6, (33-37), Online publication date: 1-Jun-2023.
- Jiao L, Zhang X, Granmo O and Abeyrathna K (2023). On the Convergence of Tsetlin Machines for the XOR Operator, IEEE Transactions on Pattern Analysis and Machine Intelligence, 45:5, (6072-6085), Online publication date: 1-May-2023.
- Pham N and Liu T Falconn++ Proceedings of the 36th International Conference on Neural Information Processing Systems, (31186-31198)
- Zarlenga M, Barbiero P, Ciravegna G, Marra G, Giannini F, Diligenti M, Shams Z, Precioso F, Melacci S, Weller A, Lio P and Jamnik M Concept embedding models Proceedings of the 36th International Conference on Neural Information Processing Systems, (21400-21413)
- Cooper M and Licato J (2022). Transformative research focus considered harmful, AI Magazine, 43:3, (273-281), Online publication date: 26-Sep-2022.
- Riera C, Rey C, Serra T, Puertas E and Pujol O Training Thinner and Deeper Neural Networks: Jumpstart Regularization Integration of Constraint Programming, Artificial Intelligence, and Operations Research, (345-357)
- Boge F (2022). Two Dimensions of Opacity and the Deep Learning Predicament, Minds and Machines, 32:1, (43-75), Online publication date: 1-Mar-2022.
- Ünal H and Başçiftçi F (2022). Evolutionary design of neural network architectures: a review of three decades of research, Artificial Intelligence Review, 55:3, (1723-1802), Online publication date: 1-Mar-2022.
- Saket R Learnability of linear thresholds from label proportions Proceedings of the 35th International Conference on Neural Information Processing Systems, (6555-6566)
- Sherstov A (2021). The hardest halfspace, Computational Complexity, 30:2, Online publication date: 1-Dec-2021.
- Crowley J Machine Learning with Neural Networks Human-Centered Artificial Intelligence, (39-54)
- Kretschmer W (2021). Lower Bounding the AND-OR Tree via Symmetrization, ACM Transactions on Computation Theory, 13:1, (1-11), Online publication date: 31-Mar-2021.
- Briot J (2020). From artificial neural networks to deep learning for music generation: history, concepts and trends, Neural Computing and Applications, 33:1, (39-65), Online publication date: 1-Jan-2021.
- Bun M and Thaler J (2021). Guest Column, ACM SIGACT News, 51:4, (48-72), Online publication date: 14-Dec-2020.
- Cano-Rocha H and Gonzalez-Garcia R (2020). Stochastic One-Step Training for Feedforward Artificial Neural Networks, Neural Processing Letters, 52:3, (2021-2041), Online publication date: 1-Dec-2020.
- Xu X, Yao Y and Cheng L Deep Learning Algorithms Design and Implementation Based on Differential Privacy Machine Learning for Cyber Security, (317-330)
- Lorena A, Garcia L, Lehmann J, Souto M and Ho T (2019). How Complex Is Your Classification Problem?, ACM Computing Surveys, 52:5, (1-34), Online publication date: 30-Sep-2020.
- Bourriaud A, Loubère R and Turpault R (2020). A Priori Neural Networks Versus A Posteriori MOOD Loop: A High Accurate 1D FV Scheme Testing Bed, Journal of Scientific Computing, 84:2, Online publication date: 3-Aug-2020.
- Asteris P and Mokos V (2019). Concrete compressive strength using artificial neural networks, Neural Computing and Applications, 32:15, (11807-11826), Online publication date: 1-Aug-2020.
- Mihret E (2020). Robotics and Artificial Intelligence, International Journal of Artificial Intelligence and Machine Learning, 10:2, (57-78), Online publication date: 1-Jul-2020.
- Solomon C, Harvey B, Kahn K, Lieberman H, Miller M, Minsky M, Papert A and Silverman B (2020). History of Logo, Proceedings of the ACM on Programming Languages, 4:HOPL, (1-66), Online publication date: 14-Jun-2020.
- Baldominos A, Saez Y and Isasi P (2019). On the automated, evolutionary design of neural networks: past, present, and future, Neural Computing and Applications, 32:2, (519-545), Online publication date: 1-Jan-2020.
- Blasch E, Cruise R, Aved A, Majumder U and Rovito T (2019). Methods of AI for Multimodal Sensing and Action for Complex Situations, AI Magazine, 40:4, (50-65), Online publication date: 1-Dec-2019.
- Lc R and Fukuoka Y Machine Learning and Therapeutic Strategies in VR Proceedings of the 9th International Conference on Digital and Interactive Arts, (1-6)
- Turner J, Floyd M, Gupta K and Oates T NOD-CC: A Hybrid CBR-CNN Architecture for Novel Object Discovery Case-Based Reasoning Research and Development, (373-387)
- Li M, Patil A, Xu K, Chaudhuri S, Khan O, Shamir A, Tu C, Chen B, Cohen-Or D and Zhang H (2019). GRAINS, ACM Transactions on Graphics, 38:2, (1-16), Online publication date: 6-Apr-2019.
- Ngo P, Passat N, Kenmochi Y and Debled-Rennesson I (2019). Geometric Preservation of 2D Digital Objects Under Rigid Motions, Journal of Mathematical Imaging and Vision, 61:2, (204-223), Online publication date: 1-Feb-2019.
- Cohen-Addad V, Feuilloley L and Starikovskaya T Lower bounds for text indexing with mismatches and differences Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, (1146-1164)
- D'Rosario M and Hsieh C (2018). Predicting Credit Rating Migration Employing Neural Network Models, International Journal of Strategic Decision Sciences, 9:4, (70-85), Online publication date: 1-Oct-2018.
- Karppa M, Kaski P and Kohonen J (2018). A Faster Subquadratic Algorithm for Finding Outlier Correlations, ACM Transactions on Algorithms, 14:3, (1-26), Online publication date: 16-Jul-2018.
- D'Rosario M and Zeleznikow J (2018). Compliance with International Soft Law, International Journal of Strategic Decision Sciences, 9:3, (1-15), Online publication date: 1-Jul-2018.
- Demongeot J and Sen S (2018). Phase transitions in stochastic non-linear threshold Boolean automata networks on Z2, Advances in Applied Mathematics, 98:C, (77-99), Online publication date: 1-Jul-2018.
- Boutry N, Géraud T and Najman L (2018). A Tutorial on Well-Composedness, Journal of Mathematical Imaging and Vision, 60:3, (443-478), Online publication date: 1-Mar-2018.
- Li K and Malik J Fast k-nearest neighbour search via prioritized DCI Proceedings of the 34th International Conference on Machine Learning - Volume 70, (2081-2090)
- R. Tavakoli H, Borji A, Laaksonen J and Rahtu E (2017). Exploiting inter-image similarity and ensemble of extreme learners for fixation prediction using deep features, Neurocomputing, 244:C, (10-18), Online publication date: 28-Jun-2017.
- D'Rosario M (2017). Fair Use Defences During Copyright Litigation, International Journal of Strategic Decision Sciences, 8:2, (31-51), Online publication date: 1-Apr-2017.
- D'Rosario M (2017). The Impact of Legal Advocacy Experience Within the US Supreme Court on Trial Decision Outcomes, International Journal of Strategic Decision Sciences, 8:1, (65-76), Online publication date: 1-Jan-2017.
- Golovko V (2017). Deep learning, Optical Memory and Neural Networks, 26:1, (1-17), Online publication date: 1-Jan-2017.
- Teuscher C (2017). The Weird, the Small, and the Uncontrollable: Redefining the Frontiers of Computing, Computer, 50:8, (52-58), Online publication date: 1-Jan-2017.
- Alan Grier D (2017). The Better Mix: 1985–1990, Computer, 50:8, (4-5), Online publication date: 1-Jan-2017.
- DeBenedictis E (2017). Computer Design Starts Over, Computer, 50:8, (14-17), Online publication date: 1-Jan-2017.
- Macukow B Neural Networks – State of Art, Brief History, Basic Models and Architecture Computer Information Systems and Industrial Management, (3-14)
- Kane D and Williams R Super-linear gate and super-quadratic wire lower bounds for depth-two and depth-three threshold circuits Proceedings of the forty-eighth annual ACM symposium on Theory of Computing, (633-643)
- Almási A, Woźniak S, Cristea V, Leblebici Y and Engbersen T (2016). Review of advances in neural networks, Neurocomputing, 174:PA, (31-41), Online publication date: 22-Jan-2016.
- Karppa M, Kaski P and Kohonen J A faster subquadratic algorithm for finding outlier correlations Proceedings of the twenty-seventh annual ACM-SIAM symposium on Discrete algorithms, (1288-1305)
- Bun M and Thaler J (2015). Dual lower bounds for approximate degree and Markov-Bernstein inequalities, Information and Computation, 243:C, (2-25), Online publication date: 1-Aug-2015.
- Hansen K and Podolskii V (2015). Polynomial threshold functions and Boolean threshold circuits, Information and Computation, 240:C, (56-73), Online publication date: 1-Feb-2015.
- Sherstov A (2014). Communication Lower Bounds Using Directional Derivatives, Journal of the ACM, 61:6, (1-71), Online publication date: 17-Dec-2014.
- Sherstov A Breaking the minsky-papert barrier for constant-depth circuits Proceedings of the forty-sixth annual ACM symposium on Theory of computing, (223-232)
- Williams R New algorithms and lower bounds for circuits with linear threshold gates Proceedings of the forty-sixth annual ACM symposium on Theory of computing, (194-202)
- Ketabdar H, Haji-Abolhassani A and Roshandel M (2013). MagiThings, International Journal of Mobile Human Computer Interaction, 5:3, (23-41), Online publication date: 1-Jul-2013.
- Zinoviev D, Benbrahim H, Meszoely G and Stefanescu D Simulating resilience in transaction-oriented networks Proceedings of the High Performance Computing Symposium, (1-5)
- Nairat M, Dahlstedt P and Nordahl M Story characterization using interactive evolution in a multi-agent system Proceedings of the Second international conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design, (168-179)
- Clifford R, Jalsenius M and Sach B Tight cell-probe bounds for online Hamming distance computation Proceedings of the twenty-fourth annual ACM-SIAM symposium on Discrete algorithms, (664-674)
- Sherstov A Making polynomials robust to noise Proceedings of the forty-fourth annual ACM symposium on Theory of computing, (747-758)
- Sherstov A The multiparty communication complexity of set disjointness Proceedings of the forty-fourth annual ACM symposium on Theory of computing, (525-548)
- Shalev-Shwartz S (2012). Online Learning and Online Convex Optimization, Foundations and Trends® in Machine Learning, 4:2, (107-194), Online publication date: 1-Feb-2012.
- Ohzeki K, Wei Y, Hirakawa Y and Sato K A new watermarking method with obfuscated quasi-chirp transform Proceedings of the 10th international conference on Digital-Forensics and Watermarking, (57-71)
- Han J, Kamber M and Pei J (2011). Data Mining, 10.5555/1972541, Online publication date: 29-Jul-2011.
- Clifford R and Jalsenius M Lower bounds for online integer multiplication and convolution in the cell-probe model Proceedings of the 38th international colloquim conference on Automata, languages and programming - Volume Part I, (593-604)
- Hadjieleftheriou M and Srivastava D (2011). Approximate String Processing, Foundations and Trends in Databases, 2:4, (267-402), Online publication date: 1-Apr-2011.
- Gelfand A, Chen Y, Welling M and Maaten L On herding and the perceptron cycling theorem Proceedings of the 24th International Conference on Neural Information Processing Systems - Volume 1, (694-702)
- Vempala S (2010). A random-sampling-based algorithm for learning intersections of halfspaces, Journal of the ACM, 57:6, (1-14), Online publication date: 1-Oct-2010.
- Sherstov A Optimal bounds for sign-representing the intersection of two halfspaces by polynomials Proceedings of the forty-second ACM symposium on Theory of computing, (523-532)
- Knoblauch A, Palm G and Sommer F (2010). Memory capacities for synaptic and structural plasticity, Neural Computation, 22:2, (289-341), Online publication date: 1-Feb-2010.
- Chen F, Chen G, He G, Xu X and He Q (2009). Universal perceptron and DNA-like learning algorithm for binary neural networks, IEEE Transactions on Neural Networks, 20:10, (1645-1658), Online publication date: 1-Oct-2009.
- Wardeh M, Bench-Capon T and Coenen F (2009). PADUA, Artificial Intelligence and Law, 17:3, (183-215), Online publication date: 1-Sep-2009.
- Beigman E and Klebanov B Learning with annotation noise Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1, (280-287)
- Brlek S, Labelle G and Lacasse A (2008). Discrete sets with minimal moment of inertia, Theoretical Computer Science, 406:1-2, (31-42), Online publication date: 20-Oct-2008.
- Zhang Y, Surendran A, Platt J and Narasimhan M Learning from multi-topic web documents for contextual advertisement Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, (1051-1059)
- Ozel Y, Guney I and Arca E Neural network solution to the cogeneration system by using coal Proceedings of the 12th WSEAS international conference on Circuits, (279-283)
- Wardeh M, Bench-Capon T and Coenen F Arguments from Experience Proceedings of the 2008 conference on Computational Models of Argument: Proceedings of COMMA 2008, (405-416)
- Achler T and Amir E Input Feedback Networks Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference, (15-26)
- Brlek S, Labelle G and Lacasse A On minimal moment of inertia polyominoes Proceedings of the 14th IAPR international conference on Discrete geometry for computer imagery, (299-309)
- Piccinini G (2008). Some neural networks compute, others don't, Neural Networks, 21:2, (311-321), Online publication date: 1-Mar-2008.
- Hillis D, McCarthy J, Mitchell T, Mueller E, Riecken D, Sloman A and Winston P (2007). In Honor of Marvin Minsky's Contributions on his 80th Birthday, AI Magazine, 28:4, (103-110), Online publication date: 1-Dec-2007.
- Hansen K Computing symmetric boolean functions by circuits with few exact threshold gates Proceedings of the 13th annual international conference on Computing and Combinatorics, (448-458)
- Ciaramita M and Attardi G Dependency parsing with second-order feature maps and annotated semantic information Proceedings of the 10th International Conference on Parsing Technologies, (133-143)
- Minsky M Form and content in computer science ACM Turing award lectures
- Vishwanathan S, Schraudolph N and Smola A (2006). Step Size Adaptation in Reproducing Kernel Hilbert Space, The Journal of Machine Learning Research, 7, (1107-1133), Online publication date: 1-Dec-2006.
- Balcan M and Blum A On a theory of learning with similarity functions Proceedings of the 23rd international conference on Machine learning, (73-80)
- Rahnamaei A, Pariz N and Akbarimajd A Detection of anthelmintics resistant nematodes in sheep flocks using artificial neural networks Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases, (27-30)
- Impagliazzo R Computational complexity since 1980 Proceedings of the 25th international conference on Foundations of Software Technology and Theoretical Computer Science, (19-47)
- Cui D and Curry D (2005). Prediction in Marketing Using the Support Vector Machine, Marketing Science, 24:4, (595-615), Online publication date: 1-Nov-2005.
- Cui D and Curry D (2005). Prediction in Marketing Using the Support Vector Machine, Marketing Science, 24:4, (595-615), Online publication date: 1-Nov-2005.
- Landy D (2005). Inside Doubt, Minds and Machines, 15:3-4, (399-414), Online publication date: 1-Nov-2005.
- Cui D and Curry D (2005). Prediction in Marketing Using the Support Vector Machine, Marketing Science, 24:4, (595-615), Online publication date: 1-Oct-2005.
- Shalev-Shwartz S and Singer Y A new perspective on an old perceptron algorithm Proceedings of the 18th annual conference on Learning Theory, (264-278)
- Eswaradass A, Sun X and Wu M A Neural Network Based Predictive Mechanism for Available Bandwidth Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
- Blum A Random projection, margins, kernels, and feature-selection Proceedings of the 2005 international conference on Subspace, Latent Structure and Feature Selection, (52-68)
- Kargupta H, Ayyagari R and Ghosh S (2004). Learning Functions Using Randomized Genetic Code-Like Transformations, IEEE Transactions on Knowledge and Data Engineering, 16:8, (894-908), Online publication date: 1-Aug-2004.
- Esmeir S and Markovitch S Lookahead-based algorithms for anytime induction of decision trees Proceedings of the twenty-first international conference on Machine learning
- Dunagan J and Vempala S A simple polynomial-time rescaling algorithm for solving linear programs Proceedings of the thirty-sixth annual ACM symposium on Theory of computing, (315-320)
- Lodding K (2004). The Hitchhiker’s Guide to Biomorphic Software, Queue, 2:4, (66-75), Online publication date: 1-Jun-2004.
- Grim P, St. Denis P and Kokalis T (2004). Information and Meaning, Minds and Machines, 14:1, (43-66), Online publication date: 1-Feb-2004.
- Barsi A Neural self-organization using graphs Proceedings of the 3rd international conference on Machine learning and data mining in pattern recognition, (343-352)
- Wang J and Gasser L Mutual online concept learning for multiple agents Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1, (362-369)
- Gams M (2002). The Turing Machine May Not Be the Universal Machine, Minds and Machines, 12:1, (137-142), Online publication date: 1-Feb-2002.
- Blum A and Dunagan J Smoothed analysis of the perceptron algorithm for linear programming Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms, (905-914)
- Pagh R On the cell probe complexity of membership and perfect hashing Proceedings of the thirty-third annual ACM symposium on Theory of computing, (425-432)
- Jin J, Kurniawati R, Xu G and Bai X (2001). Using Browsing to Improve Content-Based Image Retrieval, Journal of Visual Communication and Image Representation, 12:2, (123-135), Online publication date: 1-Jun-2001.
- Philip N and Joseph K (2000). Boosting the differences: A fast Bayesian classifier neural network, Intelligent Data Analysis, 4:6, (463-473), Online publication date: 1-Dec-2000.
- Freund Y and Schapire R (1999). Large Margin Classification Using the Perceptron Algorithm, Machine Language, 37:3, (277-296), Online publication date: 1-Dec-1999.
- Arriaga R and Vempala S An Algorithmic Theory of Learning Proceedings of the 40th Annual Symposium on Foundations of Computer Science
- Schlagel R (1999). Why not Artificial Consciousness or Thought?, Minds and Machines, 9:1, (3-28), Online publication date: 1-Feb-1999.
- Kaplan H, Strauss M and Szegedy M Just the fax—differentiating voice and fax phone lines using call billing data Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms, (935-936)
- Latecki L, Conrad C and Gross A (1998). Preserving Topology by a Digitization Process, Journal of Mathematical Imaging and Vision, 8:2, (131-159), Online publication date: 1-Mar-1998.
- Raghavan V and Sever H On the reuse of past optimal queries Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval, (344-350)
- Raghunath K and Cherkassky V (1994). Noise Performance of Linear Associative Memories, IEEE Transactions on Pattern Analysis and Machine Intelligence, 16:7, (757-765), Online publication date: 1-Jul-1994.
- Kulkarni S, Mitter S, Richardson R and Tsitsiklis J (1994). Local Versus Nonlocal Computation of Length of Digitized Curves, IEEE Transactions on Pattern Analysis and Machine Intelligence, 16:7, (711-718), Online publication date: 1-Jul-1994.
- Hussain B and Kabuka M (1994). A Novel Feature Recognition Neural Network and its Application to Character Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, 16:1, (98-106), Online publication date: 1-Jan-1994.
- Church K and Mercer R (1993). Introduction to the special issue on computational linguistics using large corpora, Computational Linguistics, 19:1, (1-24), Online publication date: 1-Mar-1993.
- Alnuweiri H and Prasanna V (1992). Parallel Architectures and Algorithms for Image Component Labeling, IEEE Transactions on Pattern Analysis and Machine Intelligence, 14:10, (1014-1034), Online publication date: 1-Oct-1992.
- Abunawass A (1992). Biologically based machine learning paradigms, ACM SIGCSE Bulletin, 24:1, (87-91), Online publication date: 1-Mar-1992.
- Abunawass A Biologically based machine learning paradigms Proceedings of the twenty-third SIGCSE technical symposium on Computer science education, (87-91)
- Eldracher M Classification of non-linear-separable real-world-problems using Δ-rule, perceptrons, and topologically distributed encoding Proceedings of the 1992 ACM/SIGAPP symposium on Applied computing: technological challenges of the 1990's, (1098-1104)
- Cherkassky V, Fassett K and Vassilas N (1991). Linear Algebra Approach to Neural Associative Memories and Noise performance of Neural Classifiers, IEEE Transactions on Computers, 40:12, (1429-1435), Online publication date: 1-Dec-1991.
- (1991). On Inexpert Systems and Natural Intelligence in Military Operations Research, Interfaces, 21:4, (2-10), Online publication date: 1-Aug-1991.
- Li D and Cellier F Fuzzy measures in inductive reasoning Proceedings of the 22nd conference on Winter simulation, (527-538)
- Wang J and Shasha D Query Processing for Distance Metrics Proceedings of the 16th International Conference on Very Large Data Bases, (602-613)
- Shvayster H (1990). Learnable and Nonlearnable Visual Concepts, IEEE Transactions on Pattern Analysis and Machine Intelligence, 12:5, (459-466), Online publication date: 1-May-1990.
- Hill W (1989). The Mind at AI, AI Magazine, 10:2, (29-41), Online publication date: 1-Jun-1989.
- Sondak N and Sondak V (1989). Neural networks and artificial intelligence, ACM SIGCSE Bulletin, 21:1, (241-245), Online publication date: 1-Feb-1989.
- Sondak N and Sondak V Neural networks and artificial intelligence Proceedings of the twentieth SIGCSE technical symposium on Computer science education, (241-245)
- Samet H and Tamminen M (1988). Efficient Component Labeling of Images of Arbitrary Dimension Represented by Linear Bintrees, IEEE Transactions on Pattern Analysis and Machine Intelligence, 10:4, (579-586), Online publication date: 1-Jul-1988.
- Gallant S (1988). Connectionist expert systems, Communications of the ACM, 31:2, (152-169), Online publication date: 1-Feb-1988.
- Blum A and Rivest R Training a 3-node neural network is NP-complete Proceedings of the 2nd International Conference on Neural Information Processing Systems, (494-501)
- Belew R A connectionist approach to conceptual information retrieval Proceedings of the 1st international conference on Artificial intelligence and law, (116-126)
- Al-Ani I, Cooley R and Awad E From decision support to expert systems Proceedings of the conference on The 1987 ACM SIGBDP-SIGCPR Conference, (10-19)
- Hanson S and Burr D Minkowski-r back-propagation Proceedings of the 1st International Conference on Neural Information Processing Systems, (348-357)
- Samet H (1984). The Quadtree and Related Hierarchical Data Structures, ACM Computing Surveys, 16:2, (187-260), Online publication date: 1-Jun-1984.
- Reiner D and Pinkerton T A method for adaptive performance improvement of operating systems Proceedings of the 1981 ACM SIGMETRICS conference on Measurement and modeling of computer systems, (2-10)
- Reiner D and Pinkerton T (1981). A method for adaptive performance improvement of operating systems, ACM SIGMETRICS Performance Evaluation Review, 10:3, (2-10), Online publication date: 1-Sep-1981.
- Ballard D (1981). Strip trees: a hierarchical representation for curves, Communications of the ACM, 24:5, (310-321), Online publication date: 1-May-1981.
- Klopf A (1975). A comparison of natural and artificial intelligence, ACM SIGART Bulletin:52, (11-13), Online publication date: 1-Jun-1975.
- Glanc A On pattern recognition and description using many sorted predicate calculi Proceedings of the ACM annual conference, (442.1-443)
- Burkhard W and Keller R (1973). Some approaches to best-match file searching, Communications of the ACM, 16:4, (230-236), Online publication date: 1-Apr-1973.
- Banerji R and Ernst G Limitations in pattern recognition and problem solving Proceedings of the ACM annual conference - Volume 1, (28-38)
- Levialdi S (1972). On shrinking binary picture patterns, Communications of the ACM, 15:1, (7-10), Online publication date: 1-Jan-1972.
Index Terms
- Perceptrons: An Introduction to Computational Geometry
Recommendations
Evolving Multilayer Perceptrons
This paper proposes a new version of a method (G-Prop, genetic backpropagation) that attempts to solve the problem of finding appropriate initial weights and learning parameters for a single hidden layer Multilayer Perceptron (MLP) by combining an ...
Designing multilayer perceptrons using a Guided Saw-tooth Evolutionary Programming Algorithm
In this paper, a diversity generating mechanism is proposed for an Evolutionary Programming (EP) algorithm that determines the basic structure of Multilayer Perceptron classifiers and simultaneously estimates the coefficients of the models. We apply a ...
Evolutionary training of hardware realizable multilayer perceptrons
The use of multilayer perceptrons (MLP) with threshold functions (binary step function activations) greatly reduces the complexity of the hardware implementation of neural networks, provides tolerance to noise and improves the interpretation of the ...