• Algorithms for coloring random and semi-random graphs 

      Subramanian, C R
      The graph coloring problem is NP-hard and arises in a variety of practical situations. Recent breakthroughs in the area of approximation complexity indicate that it is not possible (unless P = NP) even to approximate the ...
    • Application of trust region on methods to learning in feed forward neural networks 

      Shevade, S K
      This thesis presents a novel algorithm for training feed-forward neural networks, addressing the limitations of the widely used back-propagation and Quickprop algorithms. While Quickprop is significantly faster than standard ...
    • Essays in applied combinatorics 

      Jayachandran, V S
      Combinatorial mathematics concerns itself with the study of discrete structures and relations. It plays a crucial role in computer science, since digital computers manipulate discrete, finite objects. The study of algorithms, ...
    • Fault tolerance in feedforward neural networks using minimax optimization 

      Deodhare, Dipti
      Neural computing is currently being proposed as a viable solution to several problems. The approach of neural computing is to capture the guiding principles that underlie the functioning of the human brain and apply them ...
    • Frames as abstractions for efficient multimedia object retrieval 

      Sivasubramanian, S
      Multimedia Information Systems (MMISs) integrate various media types - text, audio, video, graphics, and animation - for machine-processable storage, retrieval, and presentation. These systems are characterized by complex ...
    • Framework for solving vehicle scheduling problems using AI techniques 

      Sasikumar, M
      Transportation resource scheduling problems are of high academic as well as practical value. These are primarily concerned with generation of movement schedules for a set of vehicles (tankers, aircraft, etc) to distribute ...