Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Harshaw, Christopher"'
A fundamental problem in network experiments is selecting an appropriate experimental design in order to precisely estimate a given causal effect of interest. In fact, optimal rates of estimation remain unknown for essentially all causal effects in n
Externí odkaz:
http://arxiv.org/abs/2411.10908
From clinical development of cancer therapies to investigations into partisan bias, adaptive sequential designs have become increasingly popular method for causal inference, as they offer the possibility of improved precision over their non-adaptive
Externí odkaz:
http://arxiv.org/abs/2305.17187
We describe a new design-based framework for drawing causal inference in randomized experiments. Causal effects in the framework are defined as linear functionals evaluated at potential outcome functions. Knowledge and assumptions about the potential
Externí odkaz:
http://arxiv.org/abs/2210.08698
Unbiased and consistent variance estimators generally do not exist for design-based treatment effect estimators because experimenters never observe more than one potential outcome for any unit. The problem is exacerbated by interference and complex e
Externí odkaz:
http://arxiv.org/abs/2112.01709
We propose subsampling as a unified algorithmic technique for submodular maximization in centralized and online settings. The idea is simple: independently sample elements from the ground set, and use simple combinatorial techniques (such as greedy o
Externí odkaz:
http://arxiv.org/abs/2104.02772
A bipartite experiment consists of one set of units being assigned treatments and another set of units for which we measure outcomes. The two sets of units are connected by a bipartite graph, governing how the treated units can affect the outcome uni
Externí odkaz:
http://arxiv.org/abs/2103.06392
We present SimultaneousGreedys, a deterministic algorithm for constrained submodular maximization. At a high level, the algorithm maintains $\ell$ solutions and greedily updates them in a simultaneous fashion. SimultaneousGreedys achieves the tightes
Externí odkaz:
http://arxiv.org/abs/2009.13998
The design of experiments involves a compromise between covariate balance and robustness. This paper provides a formalization of this trade-off and describes an experimental design that allows experimenters to navigate it. The design is specified by
Externí odkaz:
http://arxiv.org/abs/1911.03071
It is generally believed that submodular functions -- and the more general class of $\gamma$-weakly submodular functions -- may only be optimized under the non-negativity assumption $f(S) \geq 0$. In this paper, we show that once the function is expr
Externí odkaz:
http://arxiv.org/abs/1904.09354
Online optimization has been a successful framework for solving large-scale problems under computational constraints and partial information. Current methods for online convex optimization require either a projection or exact gradient computation at
Externí odkaz:
http://arxiv.org/abs/1802.08183