2.9k citations · 3.2k across the 12 of their papers we have counts for
12 papers
On the Factory Floor: ML Engineering for Industrial-Scale Ads Recommendation Models
Rohan Anil, Sandra Gadanho, Da Huang +9
For industrial-scale advertising systems, prediction of ad click-through rate (CTR) is a central problem. Ad clicks constitute a significant class of user engagements and are often…
How Important Is a Neuron?
Kedar Dhamdhere, Mukund Sundararajan, Qiqi Yan
The problem of attributing a deep network's prediction to its \emph{input/base} features is well-studied. We introduce the notion of \emph{conductance} to extend the notion of attr…
A Simple and Efficient MapReduce Algorithm for Data Cube Materialization
Mukund Sundararajan, Qiqi Yan
Data cube materialization is a classical database operator introduced in Gray et al.~(Data Mining and Knowledge Discovery, Vol.~1), which is critical for many analysis tasks. Nandi…
Hierarchical Summarization of Metric Changes
Matthias Ruhl, Mukund Sundararajan, Qiqi Yan
We study changes in metrics that are defined on a cartesian product of trees. Such metrics occur naturally in many practical applications, where a global metric (such as revenue) c…
Axiomatic Attribution for Deep Networks
Mukund Sundararajan, Ankur Taly, Qiqi Yan
We study the problem of attributing the prediction of a deep network to its input features, a problem previously studied by several other works. We identify two fundamental axioms-…
Gradients of Counterfactuals
Mukund Sundararajan, Ankur Taly, Qiqi Yan
Gradients have been used to quantify feature importance in machine learning models. Unfortunately, in nonlinear deep networks, not only individual neurons but also the whole networ…
Envy Freedom and Prior-free Mechanism Design
Nikhil R. Devanur, Jason D. Hartline, Qiqi Yan
We consider the provision of an abstract service to single-dimensional agents. Our model includes position auctions, single-minded combinatorial auctions, and constrained matching…
An approximately truthful-in-expectation mechanism for combinatorial auctions using value queries
Shaddin Dughmi, Tim Roughgarden, Jan Vondrak +1
This manuscript presents an alternative implementation of the truthful-in-expectation mechanism of Dughmi, Roughgarden and Yan for combinatorial auctions with weighted-matroid-rank…
From Convex Optimization to Randomized Mechanisms: Toward Optimal Combinatorial Auctions
Shaddin Dughmi, Tim Roughgarden, Qiqi Yan
We design an expected polynomial-time, truthful-in-expectation, (1-1/e)-approximation mechanism for welfare maximization in a fundamental class of combinatorial auctions. Our resul…
Mechanism Design via Correlation Gap
Qiqi Yan
For revenue and welfare maximization in single-dimensional Bayesian settings, Chawla et al. (STOC10) recently showed that sequential posted-price mechanisms (SPMs), though simple i…
Robust Mechanisms for Risk-Averse Sellers
Mukund Sundararajan, Qiqi Yan
The existing literature on optimal auctions focuses on optimizing the expected revenue of the seller, and is appropriate for risk-neutral sellers. In this paper, we identify good m…
Lower Bounds for Complementation of omega-Automata Via the Full Automata Technique
Qiqi Yan
In this paper, we first introduce a lower bound technique for the state complexity of transformations of automata. Namely we suggest first considering the class of full automata in…