Search Results for author:
Found 8 papers, 1 papers with code
EMC$^2$: Efficient MCMC Negative Sampling for Contrastive Learning with Global Convergence
We follow the global contrastive learning loss as introduced in SogCLR, and propose EMC$^2$ which utilizes an adaptive Metropolis-Hastings subroutine to generate hardness-aware negative samples in an online fashion during the optimization.
Testing the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks
Tables stored in databases and tables which are present in web pages and articles account for a large part of semi-structured data that is available on the internet.
HYTREL: Hypergraph-enhanced Tabular Data Representation Learning
Language models pretrained on large collections of tabular data have demonstrated their effectiveness in several downstream tasks.
An Algorithm For Adversary Aware Decentralized Networked MARL
Decentralized multi-agent reinforcement learning (MARL) algorithms have become popular in the literature since it allows heterogeneous agents to have their own reward functions as opposed to canonical multi-agent Markov Decision Process (MDP) settings which assume common reward functions over all agents.
Parameter and Data Efficient Continual Pre-training for Robustness to Dialectal Variance in Arabic
While prior research studies have tried to adapt these multilingual models for dialectal variants of Arabic, it still remains a challenging problem owing to the lack of sufficient monolingual dialectal data and parallel translation data of such dialectal variants.
Bandit based centralized matching in two-sided markets for peer to peer lending
We study investment designs in two sided platforms using matching markets when the investors or lenders also face restrictions on the investments based on borrower preferences.
Bandits in Matching Markets: Ideas and Proposals for Peer Lending
Motivated by recent applications of sequential decision making in matching markets, in this paper we attempt at formulating and abstracting market designs for P2P lending.
Mitigating Bias in Online Microfinance Platforms: A Case Study on Kiva.org
We find that the influence from economic factors and loan attributes can have substantially different roles to play for different sectors in achieving faster funding.
