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Found 16 papers, 3 papers with code
Optimal Top-Two Method for Best Arm Identification and Fluid Analysis
We show that the proposed algorithm is optimal as $\delta \rightarrow 0$.
Comparing skill of historical rainfall data based monsoon rainfall prediction in India with NCEP-NWP forecasts
On average, compared to our predictions, forecasts from NCEP-NWP model have about 34% higher error for a single day prediction, and over 68% higher error for a three day prediction.
Optimal Best-Arm Identification in Bandits with Access to Offline Data
Learning paradigms based purely on offline data as well as those based solely on sequential online learning have been well-studied in the literature.
Agent based simulators for epidemic modelling: Simulating larger models using smaller ones
They provide the flexibility to accurately model a heterogeneous population with time and location varying, person-specific interactions as well as detailed governmental mobility restrictions.
Potential 3rd COVID Wave in Mumbai: Scenario Analysis
Due to uncertainties regarding emergence of new variants and reinfections, instead of projecting our best guess scenario, in this report we conduct an extensive scenario analysis for Mumbai and track peak fatalities in the coming months in each of these scenarios.
Modelling the Second Covid-19 Wave in Mumbai
We use our simulator to conduct an extensive scenario analysis - we play out many plausible scenarios through varying economic activity, reinfection levels, population compliance, infectiveness, prevalence and lethality of the possible variant strains, and infection spread via local trains to arrive at those that may better explain the second wave fatality numbers.
Regret Minimization in Heavy-Tailed Bandits
We show that our index concentrates faster than the well known truncated or trimmed empirical mean estimators for the mean of heavy-tailed distributions.
COVID-19 Epidemic in Mumbai: Projections, full economic opening, and containment zones versus contact tracing and testing: An Update
These projections were developed taking into account a possible second wave if the economy and the local trains are fully opened either on November 1, 2020 or on January 1, 2021.
Physics and Society Populations and Evolution
Optimal Best-Arm Identification Methods for Tail-Risk Measures
Conditional value-at-risk (CVaR) and value-at-risk (VaR) are popular tail-risk measures in finance and insurance industries as well as in highly reliable, safety-critical uncertain environments where often the underlying probability distributions are heavy-tailed.
City-Scale Agent-Based Simulators for the Study of Non-Pharmaceutical Interventions in the Context of the COVID-19 Epidemic
We highlight the usefulness of city-scale agent-based simulators in studying various non-pharmaceutical interventions to manage an evolving pandemic.
Populations and Evolution Other Computer Science Physics and Society Quantitative Methods
COVID-19 Epidemic Study II: Phased Emergence From the Lockdown in Mumbai
In an earlier IISc-TIFR Report, we presented an agent-based city-scale simulator(ABCS) to model the progression and spread of the infection in large metropolises like Mumbai and Bengaluru.
Discriminative Learning via Adaptive Questioning
We consider this problem from a fixed confidence-based $\delta$-correct framework, that in our setting seeks to arrive at the correct ability discrimination at the fastest possible rate while guaranteeing that the probability of error is less than a pre-specified and small $\delta$.
Credit Risk: Simple Closed Form Approximate Maximum Likelihood Estimator
In a practically reasonable asymptotic regime where the default probabilities are small, say 1-3% annually, the number of firms and the time period of data available is reasonably large, we rigorously show that the proposed estimator behaves similarly or slightly worse than the MLE when the underlying model is correctly specified.
Optimal $δ$-Correct Best-Arm Selection for Heavy-Tailed Distributions
We then propose a $\delta$-correct algorithm that matches the lower bound as $\delta$ reduces to zero under the mild restriction that a known bound on the expectation of $(1+\epsilon)^{th}$ moment of the underlying random variables exists, for $\epsilon > 0$.
Sample complexity of partition identification using multi-armed bandits
We consider distributions belonging to the single parameter exponential family and primarily consider partitions where the vector of means of arms lie either in a given set or its complement.
Selecting the best system and multi-armed bandits
Consider the problem of finding a population or a probability distribution amongst many with the largest mean when these means are unknown but population samples can be simulated or otherwise generated.
