These hyper-networks pose great challenges to existing network embedding methods when the hyperedges are indecomposable, that is to say, any subset of nodes in a hyperedge cannot form another hyperedge. In real world, however, the relationships among data points could go beyond pairwise, i.e., three or more objects are involved in each relationship represented by a hyperedge, thus forming hyper-networks. Existing network embedding methods mainly focus on networks with pairwise relationships. Network embedding has recently attracted lots of attentions in data mining. Our algorithm outperforms competing methods in terms of scalability and solution quality and finds near-optimal strategies for the control of the HWA for fine-grained networks - an important problem in computational sustainability. We evaluate our contributions in the context of biocontrol for the insect pest Hemlock Wolly Adelgid (HWA) in eastern North America. Available methods based on continuous relaxations scale poorly, to remedy this we develop a novel and scalable randomized algorithm based on a width relaxation, applicable to a broad class of combinatorial optimization problems. Recurring budgets, which typically face conservation organizations, naturally leads to sparse constraints which make the problem amenable to approximation algorithms.
We formulate and study a nonlinear problem of optimal biocontrol: optimally seeding the predator cascade over time to minimize the harmful prey population. The most promising management strategy is often biocontrol, which entails introducing a natural predator able to control the invading population, a setting that can be treated as two interacting cascades of predator and prey populations. A cascading phenomenon of ecological and economic impact is the spread of invasive species in geographic landscapes. TweetĬascades represent rapid changes in networks. We also consider the two limit cases where the agent can survive with probability 0 or 1, and provide specialized algorithms to detect these kinds of situations more efficiently. We study the computational complexity of the problem, and present two algorithms for computing high quality solutions in the general case: an exact algorithm based on Mixed-Integer Nonlinear Programming, working well in instances of moderate size, and a pseudo-polynomial time heuristic algorithm allowing to solve large scale problems in reasonable time. Given a goal vertex and a deadline to reach it, the agent must compute the path to the goal that maximizes its chances of survival. a robot) must reach a given destination while avoiding being intercepted by probabilistic entities which exist in the graph with a given probability and move according to a probabilistic motion pattern known a priori. We consider a setting where an agent (e.g.
Wristbands are required for entry into all In-Person Group Fitness classes and are available beginning 30 minutes prior to the scheduled start time for each class. Wristbands may be obtained in the following locations:įor classes in Appel Commons (3rd Floor Multipurpose Room and Fitness Center).įor classes in Noyes Community Recreation Center.įor classes in Bartels Hall - Ramin Room.This paper introduces and studies a graph-based variant of the path planning problem arising in hostile environments. When wearing a mask, some find it more comfortable to exercise when they pair a mask with a 3D silicone bracket support frame, as it supports the mask away from the mouth.See In-Person Group Fitness Classes COVID-19 Policies. Beginning Mafully vaccinated/boosted members & instructors are no longer required to wear masks.CFC Membership or a Cornell Wellness Recreation Membership is required to attend all In-Person Group Fitness classes.You can access those classes on Wellness' Healthy Living Program webpage. Looking for additional low to moderate intensity virtual group fitness class options? Wellness' Healthy Living Program is also offering classes including Barre, Muscle Pump, Power H.I.I.T., Yoga and ZUMBA ® Gold.