A profile matching algorithm takes as input a user profile of one social network and returns, if existing, the profile of the same person in another social network. Such methods have immediate applications in Internet marketing, search, security, and a number of other domains, which is why this topic saw a recent surge in popularity.…
Temporal localization remains an important challenge in video understanding. In this work, we present our solution to the 3rd YouTube-8M Video Understanding Challenge organized by Google Research. Participants were required to build a segment-level classifier using a large-scale training data set with noisy video-level labels and a relatively small-scale validation data set with accurate segment-level…
Neural network interpretability is a vital component for applications across a wide variety of domains. In such cases it is often useful to analyze a network which has already been trained for its specific purpose. In this work, we develop a method to produce explanation masks for pre-trained networks. The mask localizes the most important…
This paper studies causal inference in randomized experiments under network interference. Most existing models of interference posit that treatments assigned to alters only affect the ego’s response through a low-dimensional exposure mapping, which only depends on units within some known network radius around the ego. We propose a substantially weaker “approximate neighborhood interference” (ANI) assumption,…
We study a seller who sets a reserve price in a second price auction with uncertainty over the joint distribution of bidders’ valuations. The seller only knows the mean of the marginal distribution of each bidder’s valuation and the range, and an adversarial nature chooses the worst-case distribution within this ambiguity set. We use a…
This paper studies inference in models of discrete choice with social interactions when the data consists of a single large network. We provide theoretical justification for the use of spatial and network HAC variance estimators in applied work, the latter constructed by using network path distance in place of spatial distance. Toward this end, we…
Distortion-based analysis has established itself as a fruitful framework for comparing voting mechanisms. m voters and n candidates are jointly embedded in an (unknown) metric space, and the voters submit rankings of candidates by non-decreasing distance from themselves. Based on the submitted rankings, the social choice rule chooses a winning candidate; the quality of the…
This paper introduces a search problem where a consumer has to first become aware of an alternative, before being able to search it. Initially, the consumer is aware of only a few alternatives. During search, the consumer sequentially decides between searching alternatives he is already aware of and expanding awareness to discover more products. I…
Recent technology advances have enabled firms to flexibly process and analyze sophisticated employee performance data at a reduced and yet significant cost. We develop a theory of optimal incentive contracting where the monitoring technology that governs the above procedure is part of the designer’s strategic planning. In otherwise standard principal-agent models with moral hazard, we…
This paper introduces a search problem where a consumer has to first become aware of an alternative, before being able to search it. Initially, the consumer is aware of only a few alternatives. During search, the consumer sequentially decides between searching alternatives he is already aware of and expanding awareness to discover more products. I…