Anupam Gupta
where else to find them
no profile links on file
what they talk about
where they keep going back
- ITCS2 editions2022–2023
all 7 in the filters
on a stage with
- Adam Tauman Kalaionce
- Han Shaoonce
- Jalani Williamsonce
all 15 in the filters
who talks about the same things
- Manish Gupta8 talks
- Anuradha Sharma3 talks
- Arun Vivek Supramanian2 talks
- Anurag Verma4 talks
- Anish Agarwal9 talks
- Varun Gupta7 talks
| title | conference | date |
|---|---|---|
| Lightning Talks! | The Role of TCS in Modern Machine Learning | 2026-05-26 |
A rapid-fire set of concrete results: an online load‑balancing scheme learns from a 1% sample and achieves a 1+ε load guarantee (using fractional relaxations… | ||
| Graph Searching with Predictions | ITCS 2023 | 2023-01-10 |
Shows that with per-node distance hints an algorithm called TreeX finds a goal in a tree with total movement O(D + Δ·e), where D is true root–goal distance, Δ… | ||
| Competitive Analysis of Online Algorithms (Part 1) | Data-Driven Decision Processes Boot Camp 2022 | 2022-08-22 |
Survey defines competitive ratio, uses rent-or-buy to show deterministic best policy buys at B days giving ratio ~2 and randomized optimal ratio is e/(e-1)… | ||
| Competitive Analysis of Online Algorithms (Part 2) | Data-Driven Decision Processes Boot Camp 2022 | 2022-08-22 |
Defines competitive analysis and proves concrete bounds: ski‑rental gets 2 - 1/B deterministically and ~e/(e-1) randomized as B→∞; cat‑and‑mouse is… | ||
| Probing to minimize | ITCS 2022 | 2022-01-31 |
Proves the first adaptive approximation for minimizing the minimum-weight element under a knapsack constraint with expected cost at most four times OPT while… | ||
| Robust Algorithms for Secretaries and Bandits | Mathematics of Online Decision Making 2020 | 2020-10-23 |
Algorithm works on a red/green model where an unknown fraction of items are adversarially timed and values are arbitrary while the rest arrive uniformly at… | ||
| Sampling Algorithms for Combinatorial Pure Exploration | Optimization, Statistics and Uncertainty | 2017-11-28 |
Takes the max-weight spanning-tree and matroid best-set problems from unknown edge means and gives sample-complexity bounds: adaptive elimination matches the… | ||
| LPs and Convex Programming Relaxations and Rounding for Stochastic Problems | Discrete Optimization via Continuous Relaxation | 2017-09-11 |
Projects exponential decision trees down to small LP surrogate for decision tree variables (marginals) and rounds them back into policies; assumes independent… | ||
| Approximation Algorithms for Optimization under Uncertainty | Uncertainty in Computation 2016 | 2016-10-04 |
Stochastic knapsack treats item sizes (and sometimes rewards) as known distributions and compares online policies to the optimal adaptive decision tree… | ||
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