16 citations · 22 across the 8 of their papers we have counts for
8 papers
A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks
Anish Saha, Konstantin Shmakov
In-context learning (ICL) enables task adaptation at inference time by conditioning on demonstrations rather than updating model parameters. Although recent time-series foundation…
A Comprehensive Forecasting Framework based on Multi-Stage Hierarchical Forecasting Reconciliation and Adjustment
Zhengchao Yang, Mithun Ghosh, Anish Saha +3
Ads demand forecasting for Walmart's ad products plays a critical role in enabling effective resource planning, allocation, and management of ads performance. In this paper, we int…
Bid Optimization for Offsite Display Ad Campaigns on eCommerce
Hangjian Li, Dong Xu, Konstantin Shmakov +2
Online retailers often use third-party demand-side-platforms (DSPs) to conduct offsite advertising and reach shoppers across the Internet on behalf of their advertisers. The proces…
Robust Consensus Clustering and its Applications for Advertising Forecasting
Deguang Kong, Miao Lu, Konstantin Shmakov +1
Consensus clustering aggregates partitions in order to find a better fit by reconciling clustering results from different sources/executions. In practice, there exist noise and out…
Do not Waste Money on Advertising Spend: Bid Recommendation via Concavity Changes
Deguang Kong, Konstantin Shmakov, Jian Yang
In computational advertising, a challenging problem is how to recommend the bid for advertisers to achieve the best return on investment (ROI) given budget constraint. This paper p…
Demystifying Advertising Campaign Bid Recommendation: A Constraint target CPA Goal Optimization
Deguang Kong, Konstantin Shmakov, Jian Yang
In cost-per-click (CPC) or cost-per-impression (CPM) advertising campaigns, advertisers always run the risk of spending the budget without getting enough conversions. Moreover, the…