Now showing items 1-6 of 6

    • Auction theory : applications to eBay 

      Pelletier, Keith K. (Rensselaer Polytechnic Institute, Troy, NY, 2011-05)
    • Complementarity formulation for sparse optimization 

      Tan, Jun (Rensselaer Polytechnic Institute, Troy, NY, 2021-12)
      Complementarity constraints are used to enforce the orthogonality between two decision vectors (or matrices). They naturally appear in mathematical programs for many applications and also in reformulations of certain ...
    • Integer optimization for the understanding and disruption of illicit networks 

      Kosmas, Daniel (Rensselaer Polytechnic Institute, Troy, NY, 2022-08)
      Tools from operations research (OR) have historically been applied to better understand and disrupt illicit trafficking networks. Two such tools are community detection and network interdiction. Community detection has ...
    • Predicting cascade size distribution on one-dimensional geographic networks 

      Treitman, Yosef (Rensselaer Polytechnic Institute, Troy, NY, 2018-08)
      We make rather specific assumptions about the distribution of agents across the geographic map and the likelihood of any pair of them being adjacent. We assume that the agents are nearly evenly spaced across the network. ...
    • Stochastic first order methods for distributed composite optimization with differential privacy 

      Sutcher-Shepard, Colin (Rensselaer Polytechnic Institute, Troy, NY, 2023-08)
      ABSTRACTDistributed optimization has gained much attention over recent years as the world generates ever more data. At the same time machine learning methods are able to solve many new problems. As the desire to train ...
    • Topics in matrix approximation 

      Nambirajan, Srinivas (Rensselaer Polytechnic Institute, Troy, NY, 2015-12)
      A fundamental need in computational linear algebra is computing with matrices quickly but approximately. This is commonly achieved by approximating matrices, either deterministically or randomly such that the structure in ...