The price of joint differential privacy in linear contextual bandits

Close the gap between regret upper and lower bounds for linear contextual bandits under joint differential privacy.

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1	{
2	"domain": "computer-science",
3	"topics": [
4	"learning-theory"
5	],
6	"type": "proof",
7	"also": [
8	"algorithm"
9	],
10	"source": {
11	"key": "colt",
12	"name": "COLT open problems",
13	"url": "https://proceedings.mlr.press/v247/azize24a.html",
14	"id": "v247/azize24a",
15	"curator": "Conference on Learning Theory (COLT)",
16	"poser": "Achraf Azize and Debabrota Basu",
17	"status": "open",
18	"as_of": "2026-10-20",
19	"catalog": "0521c19bbd38"
20	},
21	"review": true,
22	"approval": "first-time"
23	}