5 citations · 7 across the 5 of their papers we have counts for
5 papers
FRACTAL: Fine-Grained Scoring from Aggregate Text Labels
Yukti Makhija, Priyanka Agrawal, Rishi Saket +1
Large language models (LLMs) are being increasingly tuned to power complex generation tasks such as writing, fact-seeking, querying and reasoning. Traditionally, human or model fee…
Hardness of Learning Boolean Functions from Label Proportions
Venkatesan Guruswami, Rishi Saket
In recent years the framework of learning from label proportions (LLP) has been gaining importance in machine learning. In this setting, the training examples are aggregated into s…
PAC Learning Linear Thresholds from Label Proportions
Anand Brahmbhatt, Rishi Saket, Aravindan Raghuveer
Learning from label proportions (LLP) is a generalization of supervised learning in which the training data is available as sets or bags of feature-vectors (instances) along with t…
Approximation Algorithms for Stochastic k-TSP
Alina Ene, Viswanath Nagarajan, Rishi Saket
We consider the stochastic -TSP problem where rewards at vertices are random and the objective is to minimize the expected length of a tour that collects reward . We present…
Stochastic Vehicle Routing with Recourse
Inge Li Goertz, Viswanath Nagarajan, Rishi Saket
We study the classic Vehicle Routing Problem in the setting of stochastic optimization with recourse. StochVRP is a two-stage optimization problem, where demand is satisfied using…